From ed3eaf365d7181194c91a8952afecfd2080cb531 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Maciej=20Jastrze=CC=A8bski?= Date: Tue, 10 Feb 2026 00:08:27 +0000 Subject: [PATCH 1/3] chore: skills cleanup --- .agents/skills/skill-creator/LICENSE.txt | 202 ------- .agents/skills/skill-creator/SKILL.md | 356 ------------ .../references/output-patterns.md | 92 --- .../skill-creator/references/workflows.md | 28 - .../skill-creator/scripts/init_skill.py | 303 ---------- .../skill-creator/scripts/package_skill.py | 110 ---- .../skill-creator/scripts/quick_validate.py | 103 ---- .claude/skills/code-review/SKILL.md | 538 ------------------ .claude/skills/doc-coauthoring/SKILL.md | 394 ------------- .claude/skills/humanizer/SKILL.md | 491 ---------------- .claude/skills/skill-creator | 1 - .gitignore | 4 + skills/react-native-testing/SKILL.md | 2 +- 13 files changed, 5 insertions(+), 2619 deletions(-) delete mode 100644 .agents/skills/skill-creator/LICENSE.txt delete mode 100644 .agents/skills/skill-creator/SKILL.md delete mode 100644 .agents/skills/skill-creator/references/output-patterns.md delete mode 100644 .agents/skills/skill-creator/references/workflows.md delete mode 100755 .agents/skills/skill-creator/scripts/init_skill.py delete mode 100755 .agents/skills/skill-creator/scripts/package_skill.py delete mode 100755 .agents/skills/skill-creator/scripts/quick_validate.py delete mode 100644 .claude/skills/code-review/SKILL.md delete mode 100644 .claude/skills/doc-coauthoring/SKILL.md delete mode 100644 .claude/skills/humanizer/SKILL.md delete mode 120000 .claude/skills/skill-creator diff --git a/.agents/skills/skill-creator/LICENSE.txt b/.agents/skills/skill-creator/LICENSE.txt deleted file mode 100644 index 7a4a3ea24..000000000 --- a/.agents/skills/skill-creator/LICENSE.txt +++ /dev/null @@ -1,202 +0,0 @@ - - Apache License - Version 2.0, January 2004 - http://www.apache.org/licenses/ - - TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION - - 1. 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This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations. -license: Complete terms in LICENSE.txt ---- - -# Skill Creator - -This skill provides guidance for creating effective skills. - -## About Skills - -Skills are modular, self-contained packages that extend Claude's capabilities by providing -specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific -domains or tasks—they transform Claude from a general-purpose agent into a specialized agent -equipped with procedural knowledge that no model can fully possess. - -### What Skills Provide - -1. Specialized workflows - Multi-step procedures for specific domains -2. Tool integrations - Instructions for working with specific file formats or APIs -3. Domain expertise - Company-specific knowledge, schemas, business logic -4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks - -## Core Principles - -### Concise is Key - -The context window is a public good. Skills share the context window with everything else Claude needs: system prompt, conversation history, other Skills' metadata, and the actual user request. - -**Default assumption: Claude is already very smart.** Only add context Claude doesn't already have. Challenge each piece of information: "Does Claude really need this explanation?" and "Does this paragraph justify its token cost?" - -Prefer concise examples over verbose explanations. - -### Set Appropriate Degrees of Freedom - -Match the level of specificity to the task's fragility and variability: - -**High freedom (text-based instructions)**: Use when multiple approaches are valid, decisions depend on context, or heuristics guide the approach. - -**Medium freedom (pseudocode or scripts with parameters)**: Use when a preferred pattern exists, some variation is acceptable, or configuration affects behavior. - -**Low freedom (specific scripts, few parameters)**: Use when operations are fragile and error-prone, consistency is critical, or a specific sequence must be followed. - -Think of Claude as exploring a path: a narrow bridge with cliffs needs specific guardrails (low freedom), while an open field allows many routes (high freedom). - -### Anatomy of a Skill - -Every skill consists of a required SKILL.md file and optional bundled resources: - -``` -skill-name/ -├── SKILL.md (required) -│ ├── YAML frontmatter metadata (required) -│ │ ├── name: (required) -│ │ ├── description: (required) -│ │ └── compatibility: (optional, rarely needed) -│ └── Markdown instructions (required) -└── Bundled Resources (optional) - ├── scripts/ - Executable code (Python/Bash/etc.) - ├── references/ - Documentation intended to be loaded into context as needed - └── assets/ - Files used in output (templates, icons, fonts, etc.) -``` - -#### SKILL.md (required) - -Every SKILL.md consists of: - -- **Frontmatter** (YAML): Contains `name` and `description` fields (required), plus optional fields like `license`, `metadata`, and `compatibility`. Only `name` and `description` are read by Claude to determine when the skill triggers, so be clear and comprehensive about what the skill is and when it should be used. The `compatibility` field is for noting environment requirements (target product, system packages, etc.) but most skills don't need it. -- **Body** (Markdown): Instructions and guidance for using the skill. Only loaded AFTER the skill triggers (if at all). - -#### Bundled Resources (optional) - -##### Scripts (`scripts/`) - -Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten. - -- **When to include**: When the same code is being rewritten repeatedly or deterministic reliability is needed -- **Example**: `scripts/rotate_pdf.py` for PDF rotation tasks -- **Benefits**: Token efficient, deterministic, may be executed without loading into context -- **Note**: Scripts may still need to be read by Claude for patching or environment-specific adjustments - -##### References (`references/`) - -Documentation and reference material intended to be loaded as needed into context to inform Claude's process and thinking. - -- **When to include**: For documentation that Claude should reference while working -- **Examples**: `references/finance.md` for financial schemas, `references/mnda.md` for company NDA template, `references/policies.md` for company policies, `references/api_docs.md` for API specifications -- **Use cases**: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides -- **Benefits**: Keeps SKILL.md lean, loaded only when Claude determines it's needed -- **Best practice**: If files are large (>10k words), include grep search patterns in SKILL.md -- **Avoid duplication**: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files. - -##### Assets (`assets/`) - -Files not intended to be loaded into context, but rather used within the output Claude produces. - -- **When to include**: When the skill needs files that will be used in the final output -- **Examples**: `assets/logo.png` for brand assets, `assets/slides.pptx` for PowerPoint templates, `assets/frontend-template/` for HTML/React boilerplate, `assets/font.ttf` for typography -- **Use cases**: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified -- **Benefits**: Separates output resources from documentation, enables Claude to use files without loading them into context - -#### What to Not Include in a Skill - -A skill should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files, including: - -- README.md -- INSTALLATION_GUIDE.md -- QUICK_REFERENCE.md -- CHANGELOG.md -- etc. - -The skill should only contain the information needed for an AI agent to do the job at hand. It should not contain auxilary context about the process that went into creating it, setup and testing procedures, user-facing documentation, etc. Creating additional documentation files just adds clutter and confusion. - -### Progressive Disclosure Design Principle - -Skills use a three-level loading system to manage context efficiently: - -1. **Metadata (name + description)** - Always in context (~100 words) -2. **SKILL.md body** - When skill triggers (<5k words) -3. **Bundled resources** - As needed by Claude (Unlimited because scripts can be executed without reading into context window) - -#### Progressive Disclosure Patterns - -Keep SKILL.md body to the essentials and under 500 lines to minimize context bloat. Split content into separate files when approaching this limit. When splitting out content into other files, it is very important to reference them from SKILL.md and describe clearly when to read them, to ensure the reader of the skill knows they exist and when to use them. - -**Key principle:** When a skill supports multiple variations, frameworks, or options, keep only the core workflow and selection guidance in SKILL.md. Move variant-specific details (patterns, examples, configuration) into separate reference files. - -**Pattern 1: High-level guide with references** - -```markdown -# PDF Processing - -## Quick start - -Extract text with pdfplumber: -[code example] - -## Advanced features - -- **Form filling**: See [FORMS.md](FORMS.md) for complete guide -- **API reference**: See [REFERENCE.md](REFERENCE.md) for all methods -- **Examples**: See [EXAMPLES.md](EXAMPLES.md) for common patterns -``` - -Claude loads FORMS.md, REFERENCE.md, or EXAMPLES.md only when needed. - -**Pattern 2: Domain-specific organization** - -For Skills with multiple domains, organize content by domain to avoid loading irrelevant context: - -``` -bigquery-skill/ -├── SKILL.md (overview and navigation) -└── reference/ - ├── finance.md (revenue, billing metrics) - ├── sales.md (opportunities, pipeline) - ├── product.md (API usage, features) - └── marketing.md (campaigns, attribution) -``` - -When a user asks about sales metrics, Claude only reads sales.md. - -Similarly, for skills supporting multiple frameworks or variants, organize by variant: - -``` -cloud-deploy/ -├── SKILL.md (workflow + provider selection) -└── references/ - ├── aws.md (AWS deployment patterns) - ├── gcp.md (GCP deployment patterns) - └── azure.md (Azure deployment patterns) -``` - -When the user chooses AWS, Claude only reads aws.md. - -**Pattern 3: Conditional details** - -Show basic content, link to advanced content: - -```markdown -# DOCX Processing - -## Creating documents - -Use docx-js for new documents. See [DOCX-JS.md](DOCX-JS.md). - -## Editing documents - -For simple edits, modify the XML directly. - -**For tracked changes**: See [REDLINING.md](REDLINING.md) -**For OOXML details**: See [OOXML.md](OOXML.md) -``` - -Claude reads REDLINING.md or OOXML.md only when the user needs those features. - -**Important guidelines:** - -- **Avoid deeply nested references** - Keep references one level deep from SKILL.md. All reference files should link directly from SKILL.md. -- **Structure longer reference files** - For files longer than 100 lines, include a table of contents at the top so Claude can see the full scope when previewing. - -## Skill Creation Process - -Skill creation involves these steps: - -1. Understand the skill with concrete examples -2. Plan reusable skill contents (scripts, references, assets) -3. Initialize the skill (run init_skill.py) -4. Edit the skill (implement resources and write SKILL.md) -5. Package the skill (run package_skill.py) -6. Iterate based on real usage - -Follow these steps in order, skipping only if there is a clear reason why they are not applicable. - -### Step 1: Understanding the Skill with Concrete Examples - -Skip this step only when the skill's usage patterns are already clearly understood. It remains valuable even when working with an existing skill. - -To create an effective skill, clearly understand concrete examples of how the skill will be used. This understanding can come from either direct user examples or generated examples that are validated with user feedback. - -For example, when building an image-editor skill, relevant questions include: - -- "What functionality should the image-editor skill support? Editing, rotating, anything else?" -- "Can you give some examples of how this skill would be used?" -- "I can imagine users asking for things like 'Remove the red-eye from this image' or 'Rotate this image'. Are there other ways you imagine this skill being used?" -- "What would a user say that should trigger this skill?" - -To avoid overwhelming users, avoid asking too many questions in a single message. Start with the most important questions and follow up as needed for better effectiveness. - -Conclude this step when there is a clear sense of the functionality the skill should support. - -### Step 2: Planning the Reusable Skill Contents - -To turn concrete examples into an effective skill, analyze each example by: - -1. Considering how to execute on the example from scratch -2. Identifying what scripts, references, and assets would be helpful when executing these workflows repeatedly - -Example: When building a `pdf-editor` skill to handle queries like "Help me rotate this PDF," the analysis shows: - -1. Rotating a PDF requires re-writing the same code each time -2. A `scripts/rotate_pdf.py` script would be helpful to store in the skill - -Example: When designing a `frontend-webapp-builder` skill for queries like "Build me a todo app" or "Build me a dashboard to track my steps," the analysis shows: - -1. Writing a frontend webapp requires the same boilerplate HTML/React each time -2. An `assets/hello-world/` template containing the boilerplate HTML/React project files would be helpful to store in the skill - -Example: When building a `big-query` skill to handle queries like "How many users have logged in today?" the analysis shows: - -1. Querying BigQuery requires re-discovering the table schemas and relationships each time -2. A `references/schema.md` file documenting the table schemas would be helpful to store in the skill - -To establish the skill's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets. - -### Step 3: Initializing the Skill - -At this point, it is time to actually create the skill. - -Skip this step only if the skill being developed already exists, and iteration or packaging is needed. In this case, continue to the next step. - -When creating a new skill from scratch, always run the `init_skill.py` script. The script conveniently generates a new template skill directory that automatically includes everything a skill requires, making the skill creation process much more efficient and reliable. - -Usage: - -```bash -scripts/init_skill.py --path -``` - -The script: - -- Creates the skill directory at the specified path -- Generates a SKILL.md template with proper frontmatter and TODO placeholders -- Creates example resource directories: `scripts/`, `references/`, and `assets/` -- Adds example files in each directory that can be customized or deleted - -After initialization, customize or remove the generated SKILL.md and example files as needed. - -### Step 4: Edit the Skill - -When editing the (newly-generated or existing) skill, remember that the skill is being created for another instance of Claude to use. Include information that would be beneficial and non-obvious to Claude. Consider what procedural knowledge, domain-specific details, or reusable assets would help another Claude instance execute these tasks more effectively. - -#### Learn Proven Design Patterns - -Consult these helpful guides based on your skill's needs: - -- **Multi-step processes**: See references/workflows.md for sequential workflows and conditional logic -- **Specific output formats or quality standards**: See references/output-patterns.md for template and example patterns - -These files contain established best practices for effective skill design. - -#### Start with Reusable Skill Contents - -To begin implementation, start with the reusable resources identified above: `scripts/`, `references/`, and `assets/` files. Note that this step may require user input. For example, when implementing a `brand-guidelines` skill, the user may need to provide brand assets or templates to store in `assets/`, or documentation to store in `references/`. - -Added scripts must be tested by actually running them to ensure there are no bugs and that the output matches what is expected. If there are many similar scripts, only a representative sample needs to be tested to ensure confidence that they all work while balancing time to completion. - -Any example files and directories not needed for the skill should be deleted. The initialization script creates example files in `scripts/`, `references/`, and `assets/` to demonstrate structure, but most skills won't need all of them. - -#### Update SKILL.md - -**Writing Guidelines:** Always use imperative/infinitive form. - -##### Frontmatter - -Write the YAML frontmatter with `name` and `description`: - -- `name`: The skill name -- `description`: This is the primary triggering mechanism for your skill, and helps Claude understand when to use the skill. - - Include both what the Skill does and specific triggers/contexts for when to use it. - - Include all "when to use" information here - Not in the body. The body is only loaded after triggering, so "When to Use This Skill" sections in the body are not helpful to Claude. - - Example description for a `docx` skill: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks" - -Do not include any other fields in YAML frontmatter. - -##### Body - -Write instructions for using the skill and its bundled resources. - -### Step 5: Packaging a Skill - -Once development of the skill is complete, it must be packaged into a distributable .skill file that gets shared with the user. The packaging process automatically validates the skill first to ensure it meets all requirements: - -```bash -scripts/package_skill.py -``` - -Optional output directory specification: - -```bash -scripts/package_skill.py ./dist -``` - -The packaging script will: - -1. **Validate** the skill automatically, checking: - - YAML frontmatter format and required fields - - Skill naming conventions and directory structure - - Description completeness and quality - - File organization and resource references - -2. **Package** the skill if validation passes, creating a .skill file named after the skill (e.g., `my-skill.skill`) that includes all files and maintains the proper directory structure for distribution. The .skill file is a zip file with a .skill extension. - -If validation fails, the script will report the errors and exit without creating a package. Fix any validation errors and run the packaging command again. - -### Step 6: Iterate - -After testing the skill, users may request improvements. Often this happens right after using the skill, with fresh context of how the skill performed. - -**Iteration workflow:** - -1. Use the skill on real tasks -2. Notice struggles or inefficiencies -3. Identify how SKILL.md or bundled resources should be updated -4. Implement changes and test again diff --git a/.agents/skills/skill-creator/references/output-patterns.md b/.agents/skills/skill-creator/references/output-patterns.md deleted file mode 100644 index 219c64c2f..000000000 --- a/.agents/skills/skill-creator/references/output-patterns.md +++ /dev/null @@ -1,92 +0,0 @@ -# Output Patterns - -Use these patterns when skills need to produce consistent, high-quality output. - -## Template Pattern - -Provide templates for output format. Match the level of strictness to your needs. - -**For strict requirements (like API responses or data formats):** - -```markdown -## Report structure - -ALWAYS use this exact template structure: - -# [Analysis Title] - -## Executive summary - -[One-paragraph overview of key findings] - -## Key findings - -- Finding 1 with supporting data -- Finding 2 with supporting data -- Finding 3 with supporting data - -## Recommendations - -1. Specific actionable recommendation -2. Specific actionable recommendation -``` - -**For flexible guidance (when adaptation is useful):** - -```markdown -## Report structure - -Here is a sensible default format, but use your best judgment: - -# [Analysis Title] - -## Executive summary - -[Overview] - -## Key findings - -[Adapt sections based on what you discover] - -## Recommendations - -[Tailor to the specific context] - -Adjust sections as needed for the specific analysis type. -``` - -## Examples Pattern - -For skills where output quality depends on seeing examples, provide input/output pairs: - -```markdown -## Commit message format - -Generate commit messages following these examples: - -**Example 1:** -Input: Added user authentication with JWT tokens -Output: -``` - -feat(auth): implement JWT-based authentication - -Add login endpoint and token validation middleware - -``` - -**Example 2:** -Input: Fixed bug where dates displayed incorrectly in reports -Output: -``` - -fix(reports): correct date formatting in timezone conversion - -Use UTC timestamps consistently across report generation - -``` - -Follow this style: type(scope): brief description, then detailed explanation. -``` - -Examples help Claude understand the desired style and level of detail more clearly than descriptions alone. diff --git a/.agents/skills/skill-creator/references/workflows.md b/.agents/skills/skill-creator/references/workflows.md deleted file mode 100644 index 54b017407..000000000 --- a/.agents/skills/skill-creator/references/workflows.md +++ /dev/null @@ -1,28 +0,0 @@ -# Workflow Patterns - -## Sequential Workflows - -For complex tasks, break operations into clear, sequential steps. It is often helpful to give Claude an overview of the process towards the beginning of SKILL.md: - -```markdown -Filling a PDF form involves these steps: - -1. Analyze the form (run analyze_form.py) -2. Create field mapping (edit fields.json) -3. Validate mapping (run validate_fields.py) -4. Fill the form (run fill_form.py) -5. Verify output (run verify_output.py) -``` - -## Conditional Workflows - -For tasks with branching logic, guide Claude through decision points: - -```markdown -1. Determine the modification type: - **Creating new content?** → Follow "Creation workflow" below - **Editing existing content?** → Follow "Editing workflow" below - -2. Creation workflow: [steps] -3. Editing workflow: [steps] -``` diff --git a/.agents/skills/skill-creator/scripts/init_skill.py b/.agents/skills/skill-creator/scripts/init_skill.py deleted file mode 100755 index c544fc725..000000000 --- a/.agents/skills/skill-creator/scripts/init_skill.py +++ /dev/null @@ -1,303 +0,0 @@ -#!/usr/bin/env python3 -""" -Skill Initializer - Creates a new skill from template - -Usage: - init_skill.py --path - -Examples: - init_skill.py my-new-skill --path skills/public - init_skill.py my-api-helper --path skills/private - init_skill.py custom-skill --path /custom/location -""" - -import sys -from pathlib import Path - - -SKILL_TEMPLATE = """--- -name: {skill_name} -description: [TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.] ---- - -# {skill_title} - -## Overview - -[TODO: 1-2 sentences explaining what this skill enables] - -## Structuring This Skill - -[TODO: Choose the structure that best fits this skill's purpose. Common patterns: - -**1. Workflow-Based** (best for sequential processes) -- Works well when there are clear step-by-step procedures -- Example: DOCX skill with "Workflow Decision Tree" → "Reading" → "Creating" → "Editing" -- Structure: ## Overview → ## Workflow Decision Tree → ## Step 1 → ## Step 2... - -**2. Task-Based** (best for tool collections) -- Works well when the skill offers different operations/capabilities -- Example: PDF skill with "Quick Start" → "Merge PDFs" → "Split PDFs" → "Extract Text" -- Structure: ## Overview → ## Quick Start → ## Task Category 1 → ## Task Category 2... - -**3. Reference/Guidelines** (best for standards or specifications) -- Works well for brand guidelines, coding standards, or requirements -- Example: Brand styling with "Brand Guidelines" → "Colors" → "Typography" → "Features" -- Structure: ## Overview → ## Guidelines → ## Specifications → ## Usage... - -**4. Capabilities-Based** (best for integrated systems) -- Works well when the skill provides multiple interrelated features -- Example: Product Management with "Core Capabilities" → numbered capability list -- Structure: ## Overview → ## Core Capabilities → ### 1. Feature → ### 2. Feature... - -Patterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations). - -Delete this entire "Structuring This Skill" section when done - it's just guidance.] - -## [TODO: Replace with the first main section based on chosen structure] - -[TODO: Add content here. See examples in existing skills: -- Code samples for technical skills -- Decision trees for complex workflows -- Concrete examples with realistic user requests -- References to scripts/templates/references as needed] - -## Resources - -This skill includes example resource directories that demonstrate how to organize different types of bundled resources: - -### scripts/ -Executable code (Python/Bash/etc.) that can be run directly to perform specific operations. - -**Examples from other skills:** -- PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation -- DOCX skill: `document.py`, `utilities.py` - Python modules for document processing - -**Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations. - -**Note:** Scripts may be executed without loading into context, but can still be read by Claude for patching or environment adjustments. - -### references/ -Documentation and reference material intended to be loaded into context to inform Claude's process and thinking. - -**Examples from other skills:** -- Product management: `communication.md`, `context_building.md` - detailed workflow guides -- BigQuery: API reference documentation and query examples -- Finance: Schema documentation, company policies - -**Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Claude should reference while working. - -### assets/ -Files not intended to be loaded into context, but rather used within the output Claude produces. - -**Examples from other skills:** -- Brand styling: PowerPoint template files (.pptx), logo files -- Frontend builder: HTML/React boilerplate project directories -- Typography: Font files (.ttf, .woff2) - -**Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output. - ---- - -**Any unneeded directories can be deleted.** Not every skill requires all three types of resources. -""" - -EXAMPLE_SCRIPT = '''#!/usr/bin/env python3 -""" -Example helper script for {skill_name} - -This is a placeholder script that can be executed directly. -Replace with actual implementation or delete if not needed. - -Example real scripts from other skills: -- pdf/scripts/fill_fillable_fields.py - Fills PDF form fields -- pdf/scripts/convert_pdf_to_images.py - Converts PDF pages to images -""" - -def main(): - print("This is an example script for {skill_name}") - # TODO: Add actual script logic here - # This could be data processing, file conversion, API calls, etc. - -if __name__ == "__main__": - main() -''' - -EXAMPLE_REFERENCE = """# Reference Documentation for {skill_title} - -This is a placeholder for detailed reference documentation. -Replace with actual reference content or delete if not needed. - -Example real reference docs from other skills: -- product-management/references/communication.md - Comprehensive guide for status updates -- product-management/references/context_building.md - Deep-dive on gathering context -- bigquery/references/ - API references and query examples - -## When Reference Docs Are Useful - -Reference docs are ideal for: -- Comprehensive API documentation -- Detailed workflow guides -- Complex multi-step processes -- Information too lengthy for main SKILL.md -- Content that's only needed for specific use cases - -## Structure Suggestions - -### API Reference Example -- Overview -- Authentication -- Endpoints with examples -- Error codes -- Rate limits - -### Workflow Guide Example -- Prerequisites -- Step-by-step instructions -- Common patterns -- Troubleshooting -- Best practices -""" - -EXAMPLE_ASSET = """# Example Asset File - -This placeholder represents where asset files would be stored. -Replace with actual asset files (templates, images, fonts, etc.) or delete if not needed. - -Asset files are NOT intended to be loaded into context, but rather used within -the output Claude produces. - -Example asset files from other skills: -- Brand guidelines: logo.png, slides_template.pptx -- Frontend builder: hello-world/ directory with HTML/React boilerplate -- Typography: custom-font.ttf, font-family.woff2 -- Data: sample_data.csv, test_dataset.json - -## Common Asset Types - -- Templates: .pptx, .docx, boilerplate directories -- Images: .png, .jpg, .svg, .gif -- Fonts: .ttf, .otf, .woff, .woff2 -- Boilerplate code: Project directories, starter files -- Icons: .ico, .svg -- Data files: .csv, .json, .xml, .yaml - -Note: This is a text placeholder. Actual assets can be any file type. -""" - - -def title_case_skill_name(skill_name): - """Convert hyphenated skill name to Title Case for display.""" - return ' '.join(word.capitalize() for word in skill_name.split('-')) - - -def init_skill(skill_name, path): - """ - Initialize a new skill directory with template SKILL.md. - - Args: - skill_name: Name of the skill - path: Path where the skill directory should be created - - Returns: - Path to created skill directory, or None if error - """ - # Determine skill directory path - skill_dir = Path(path).resolve() / skill_name - - # Check if directory already exists - if skill_dir.exists(): - print(f"❌ Error: Skill directory already exists: {skill_dir}") - return None - - # Create skill directory - try: - skill_dir.mkdir(parents=True, exist_ok=False) - print(f"✅ Created skill directory: {skill_dir}") - except Exception as e: - print(f"❌ Error creating directory: {e}") - return None - - # Create SKILL.md from template - skill_title = title_case_skill_name(skill_name) - skill_content = SKILL_TEMPLATE.format( - skill_name=skill_name, - skill_title=skill_title - ) - - skill_md_path = skill_dir / 'SKILL.md' - try: - skill_md_path.write_text(skill_content) - print("✅ Created SKILL.md") - except Exception as e: - print(f"❌ Error creating SKILL.md: {e}") - return None - - # Create resource directories with example files - try: - # Create scripts/ directory with example script - scripts_dir = skill_dir / 'scripts' - scripts_dir.mkdir(exist_ok=True) - example_script = scripts_dir / 'example.py' - example_script.write_text(EXAMPLE_SCRIPT.format(skill_name=skill_name)) - example_script.chmod(0o755) - print("✅ Created scripts/example.py") - - # Create references/ directory with example reference doc - references_dir = skill_dir / 'references' - references_dir.mkdir(exist_ok=True) - example_reference = references_dir / 'api_reference.md' - example_reference.write_text(EXAMPLE_REFERENCE.format(skill_title=skill_title)) - print("✅ Created references/api_reference.md") - - # Create assets/ directory with example asset placeholder - assets_dir = skill_dir / 'assets' - assets_dir.mkdir(exist_ok=True) - example_asset = assets_dir / 'example_asset.txt' - example_asset.write_text(EXAMPLE_ASSET) - print("✅ Created assets/example_asset.txt") - except Exception as e: - print(f"❌ Error creating resource directories: {e}") - return None - - # Print next steps - print(f"\n✅ Skill '{skill_name}' initialized successfully at {skill_dir}") - print("\nNext steps:") - print("1. Edit SKILL.md to complete the TODO items and update the description") - print("2. Customize or delete the example files in scripts/, references/, and assets/") - print("3. Run the validator when ready to check the skill structure") - - return skill_dir - - -def main(): - if len(sys.argv) < 4 or sys.argv[2] != '--path': - print("Usage: init_skill.py --path ") - print("\nSkill name requirements:") - print(" - Kebab-case identifier (e.g., 'my-data-analyzer')") - print(" - Lowercase letters, digits, and hyphens only") - print(" - Max 64 characters") - print(" - Must match directory name exactly") - print("\nExamples:") - print(" init_skill.py my-new-skill --path skills/public") - print(" init_skill.py my-api-helper --path skills/private") - print(" init_skill.py custom-skill --path /custom/location") - sys.exit(1) - - skill_name = sys.argv[1] - path = sys.argv[3] - - print(f"🚀 Initializing skill: {skill_name}") - print(f" Location: {path}") - print() - - result = init_skill(skill_name, path) - - if result: - sys.exit(0) - else: - sys.exit(1) - - -if __name__ == "__main__": - main() diff --git a/.agents/skills/skill-creator/scripts/package_skill.py b/.agents/skills/skill-creator/scripts/package_skill.py deleted file mode 100755 index 5cd36cb16..000000000 --- a/.agents/skills/skill-creator/scripts/package_skill.py +++ /dev/null @@ -1,110 +0,0 @@ -#!/usr/bin/env python3 -""" -Skill Packager - Creates a distributable .skill file of a skill folder - -Usage: - python utils/package_skill.py [output-directory] - -Example: - python utils/package_skill.py skills/public/my-skill - python utils/package_skill.py skills/public/my-skill ./dist -""" - -import sys -import zipfile -from pathlib import Path -from quick_validate import validate_skill - - -def package_skill(skill_path, output_dir=None): - """ - Package a skill folder into a .skill file. - - Args: - skill_path: Path to the skill folder - output_dir: Optional output directory for the .skill file (defaults to current directory) - - Returns: - Path to the created .skill file, or None if error - """ - skill_path = Path(skill_path).resolve() - - # Validate skill folder exists - if not skill_path.exists(): - print(f"❌ Error: Skill folder not found: {skill_path}") - return None - - if not skill_path.is_dir(): - print(f"❌ Error: Path is not a directory: {skill_path}") - return None - - # Validate SKILL.md exists - skill_md = skill_path / "SKILL.md" - if not skill_md.exists(): - print(f"❌ Error: SKILL.md not found in {skill_path}") - return None - - # Run validation before packaging - print("🔍 Validating skill...") - valid, message = validate_skill(skill_path) - if not valid: - print(f"❌ Validation failed: {message}") - print(" Please fix the validation errors before packaging.") - return None - print(f"✅ {message}\n") - - # Determine output location - skill_name = skill_path.name - if output_dir: - output_path = Path(output_dir).resolve() - output_path.mkdir(parents=True, exist_ok=True) - else: - output_path = Path.cwd() - - skill_filename = output_path / f"{skill_name}.skill" - - # Create the .skill file (zip format) - try: - with zipfile.ZipFile(skill_filename, 'w', zipfile.ZIP_DEFLATED) as zipf: - # Walk through the skill directory - for file_path in skill_path.rglob('*'): - if file_path.is_file(): - # Calculate the relative path within the zip - arcname = file_path.relative_to(skill_path.parent) - zipf.write(file_path, arcname) - print(f" Added: {arcname}") - - print(f"\n✅ Successfully packaged skill to: {skill_filename}") - return skill_filename - - except Exception as e: - print(f"❌ Error creating .skill file: {e}") - return None - - -def main(): - if len(sys.argv) < 2: - print("Usage: python utils/package_skill.py [output-directory]") - print("\nExample:") - print(" python utils/package_skill.py skills/public/my-skill") - print(" python utils/package_skill.py skills/public/my-skill ./dist") - sys.exit(1) - - skill_path = sys.argv[1] - output_dir = sys.argv[2] if len(sys.argv) > 2 else None - - print(f"📦 Packaging skill: {skill_path}") - if output_dir: - print(f" Output directory: {output_dir}") - print() - - result = package_skill(skill_path, output_dir) - - if result: - sys.exit(0) - else: - sys.exit(1) - - -if __name__ == "__main__": - main() diff --git a/.agents/skills/skill-creator/scripts/quick_validate.py b/.agents/skills/skill-creator/scripts/quick_validate.py deleted file mode 100755 index ed8e1dddc..000000000 --- a/.agents/skills/skill-creator/scripts/quick_validate.py +++ /dev/null @@ -1,103 +0,0 @@ -#!/usr/bin/env python3 -""" -Quick validation script for skills - minimal version -""" - -import sys -import os -import re -import yaml -from pathlib import Path - -def validate_skill(skill_path): - """Basic validation of a skill""" - skill_path = Path(skill_path) - - # Check SKILL.md exists - skill_md = skill_path / 'SKILL.md' - if not skill_md.exists(): - return False, "SKILL.md not found" - - # Read and validate frontmatter - content = skill_md.read_text() - if not content.startswith('---'): - return False, "No YAML frontmatter found" - - # Extract frontmatter - match = re.match(r'^---\n(.*?)\n---', content, re.DOTALL) - if not match: - return False, "Invalid frontmatter format" - - frontmatter_text = match.group(1) - - # Parse YAML frontmatter - try: - frontmatter = yaml.safe_load(frontmatter_text) - if not isinstance(frontmatter, dict): - return False, "Frontmatter must be a YAML dictionary" - except yaml.YAMLError as e: - return False, f"Invalid YAML in frontmatter: {e}" - - # Define allowed properties - ALLOWED_PROPERTIES = {'name', 'description', 'license', 'allowed-tools', 'metadata', 'compatibility'} - - # Check for unexpected properties (excluding nested keys under metadata) - unexpected_keys = set(frontmatter.keys()) - ALLOWED_PROPERTIES - if unexpected_keys: - return False, ( - f"Unexpected key(s) in SKILL.md frontmatter: {', '.join(sorted(unexpected_keys))}. " - f"Allowed properties are: {', '.join(sorted(ALLOWED_PROPERTIES))}" - ) - - # Check required fields - if 'name' not in frontmatter: - return False, "Missing 'name' in frontmatter" - if 'description' not in frontmatter: - return False, "Missing 'description' in frontmatter" - - # Extract name for validation - name = frontmatter.get('name', '') - if not isinstance(name, str): - return False, f"Name must be a string, got {type(name).__name__}" - name = name.strip() - if name: - # Check naming convention (kebab-case: lowercase with hyphens) - if not re.match(r'^[a-z0-9-]+$', name): - return False, f"Name '{name}' should be kebab-case (lowercase letters, digits, and hyphens only)" - if name.startswith('-') or name.endswith('-') or '--' in name: - return False, f"Name '{name}' cannot start/end with hyphen or contain consecutive hyphens" - # Check name length (max 64 characters per spec) - if len(name) > 64: - return False, f"Name is too long ({len(name)} characters). Maximum is 64 characters." - - # Extract and validate description - description = frontmatter.get('description', '') - if not isinstance(description, str): - return False, f"Description must be a string, got {type(description).__name__}" - description = description.strip() - if description: - # Check for angle brackets - if '<' in description or '>' in description: - return False, "Description cannot contain angle brackets (< or >)" - # Check description length (max 1024 characters per spec) - if len(description) > 1024: - return False, f"Description is too long ({len(description)} characters). Maximum is 1024 characters." - - # Validate compatibility field if present (optional) - compatibility = frontmatter.get('compatibility', '') - if compatibility: - if not isinstance(compatibility, str): - return False, f"Compatibility must be a string, got {type(compatibility).__name__}" - if len(compatibility) > 500: - return False, f"Compatibility is too long ({len(compatibility)} characters). Maximum is 500 characters." - - return True, "Skill is valid!" - -if __name__ == "__main__": - if len(sys.argv) != 2: - print("Usage: python quick_validate.py ") - sys.exit(1) - - valid, message = validate_skill(sys.argv[1]) - print(message) - sys.exit(0 if valid else 1) \ No newline at end of file diff --git a/.claude/skills/code-review/SKILL.md b/.claude/skills/code-review/SKILL.md deleted file mode 100644 index 309234e57..000000000 --- a/.claude/skills/code-review/SKILL.md +++ /dev/null @@ -1,538 +0,0 @@ ---- -name: code-review-excellence -description: Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers. ---- - -# Code Review Excellence - -Transform code reviews from gatekeeping to knowledge sharing through constructive feedback, systematic analysis, and collaborative improvement. - -## When to Use This Skill - -- Reviewing pull requests and code changes -- Establishing code review standards for teams -- Mentoring junior developers through reviews -- Conducting architecture reviews -- Creating review checklists and guidelines -- Improving team collaboration -- Reducing code review cycle time -- Maintaining code quality standards - -## Core Principles - -### 1. The Review Mindset - -**Goals of Code Review:** - -- Catch bugs and edge cases -- Ensure code maintainability -- Share knowledge across team -- Enforce coding standards -- Improve design and architecture -- Build team culture - -**Not the Goals:** - -- Show off knowledge -- Nitpick formatting (use linters) -- Block progress unnecessarily -- Rewrite to your preference - -### 2. Effective Feedback - -**Good Feedback is:** - -- Specific and actionable -- Educational, not judgmental -- Focused on the code, not the person -- Balanced (praise good work too) -- Prioritized (critical vs nice-to-have) - -```markdown -❌ Bad: "This is wrong." -✅ Good: "This could cause a race condition when multiple users -access simultaneously. Consider using a mutex here." - -❌ Bad: "Why didn't you use X pattern?" -✅ Good: "Have you considered the Repository pattern? It would -make this easier to test. Here's an example: [link]" - -❌ Bad: "Rename this variable." -✅ Good: "[nit] Consider `userCount` instead of `uc` for -clarity. Not blocking if you prefer to keep it." -``` - -### 3. Review Scope - -**What to Review:** - -- Logic correctness and edge cases -- Security vulnerabilities -- Performance implications -- Test coverage and quality -- Error handling -- Documentation and comments -- API design and naming -- Architectural fit - -**What Not to Review Manually:** - -- Code formatting (use Prettier, Black, etc.) -- Import organization -- Linting violations -- Simple typos - -## Review Process - -### Phase 1: Context Gathering (2-3 minutes) - -```markdown -Before diving into code, understand: - -1. Read PR description and linked issue -2. Check PR size (>400 lines? Ask to split) -3. Review CI/CD status (tests passing?) -4. Understand the business requirement -5. Note any relevant architectural decisions -``` - -### Phase 2: High-Level Review (5-10 minutes) - -```markdown -1. **Architecture & Design** - - Does the solution fit the problem? - - Are there simpler approaches? - - Is it consistent with existing patterns? - - Will it scale? - -2. **File Organization** - - Are new files in the right places? - - Is code grouped logically? - - Are there duplicate files? - -3. **Testing Strategy** - - Are there tests? - - Do tests cover edge cases? - - Are tests readable? -``` - -### Phase 3: Line-by-Line Review (10-20 minutes) - -```markdown -For each file: - -1. **Logic & Correctness** - - Edge cases handled? - - Off-by-one errors? - - Null/undefined checks? - - Race conditions? - -2. **Security** - - Input validation? - - SQL injection risks? - - XSS vulnerabilities? - - Sensitive data exposure? - -3. **Performance** - - N+1 queries? - - Unnecessary loops? - - Memory leaks? - - Blocking operations? - -4. **Maintainability** - - Clear variable names? - - Functions doing one thing? - - Complex code commented? - - Magic numbers extracted? -``` - -### Phase 4: Summary & Decision (2-3 minutes) - -```markdown -1. Summarize key concerns -2. Highlight what you liked -3. Make clear decision: - - ✅ Approve - - 💬 Comment (minor suggestions) - - 🔄 Request Changes (must address) -4. Offer to pair if complex -``` - -## Review Techniques - -### Technique 1: The Checklist Method - -```markdown -## Security Checklist - -- [ ] User input validated and sanitized -- [ ] SQL queries use parameterization -- [ ] Authentication/authorization checked -- [ ] Secrets not hardcoded -- [ ] Error messages don't leak info - -## Performance Checklist - -- [ ] No N+1 queries -- [ ] Database queries indexed -- [ ] Large lists paginated -- [ ] Expensive operations cached -- [ ] No blocking I/O in hot paths - -## Testing Checklist - -- [ ] Happy path tested -- [ ] Edge cases covered -- [ ] Error cases tested -- [ ] Test names are descriptive -- [ ] Tests are deterministic -``` - -### Technique 2: The Question Approach - -Instead of stating problems, ask questions to encourage thinking: - -```markdown -❌ "This will fail if the list is empty." -✅ "What happens if `items` is an empty array?" - -❌ "You need error handling here." -✅ "How should this behave if the API call fails?" - -❌ "This is inefficient." -✅ "I see this loops through all users. Have we considered -the performance impact with 100k users?" -``` - -### Technique 3: Suggest, Don't Command - -```markdown -## Use Collaborative Language - -❌ "You must change this to use async/await" -✅ "Suggestion: async/await might make this more readable: -`typescript - async function fetchUser(id: string) { - const user = await db.query('SELECT * FROM users WHERE id = ?', id); - return user; - } - ` -What do you think?" - -❌ "Extract this into a function" -✅ "This logic appears in 3 places. Would it make sense to -extract it into a shared utility function?" -``` - -### Technique 4: Differentiate Severity - -```markdown -Use labels to indicate priority: - -🔴 [blocking] - Must fix before merge -🟡 [important] - Should fix, discuss if disagree -🟢 [nit] - Nice to have, not blocking -💡 [suggestion] - Alternative approach to consider -📚 [learning] - Educational comment, no action needed -🎉 [praise] - Good work, keep it up! - -Example: -"🔴 [blocking] This SQL query is vulnerable to injection. -Please use parameterized queries." - -"🟢 [nit] Consider renaming `data` to `userData` for clarity." - -"🎉 [praise] Excellent test coverage! This will catch edge cases." -``` - -## Language-Specific Patterns - -### Python Code Review - -```python -# Check for Python-specific issues - -# ❌ Mutable default arguments -def add_item(item, items=[]): # Bug! Shared across calls - items.append(item) - return items - -# ✅ Use None as default -def add_item(item, items=None): - if items is None: - items = [] - items.append(item) - return items - -# ❌ Catching too broad -try: - result = risky_operation() -except: # Catches everything, even KeyboardInterrupt! - pass - -# ✅ Catch specific exceptions -try: - result = risky_operation() -except ValueError as e: - logger.error(f"Invalid value: {e}") - raise - -# ❌ Using mutable class attributes -class User: - permissions = [] # Shared across all instances! - -# ✅ Initialize in __init__ -class User: - def __init__(self): - self.permissions = [] -``` - -### TypeScript/JavaScript Code Review - -```typescript -// Check for TypeScript-specific issues - -// ❌ Using any defeats type safety -function processData(data: any) { // Avoid any - return data.value; -} - -// ✅ Use proper types -interface DataPayload { - value: string; -} -function processData(data: DataPayload) { - return data.value; -} - -// ❌ Not handling async errors -async function fetchUser(id: string) { - const response = await fetch(`/api/users/${id}`); - return response.json(); // What if network fails? -} - -// ✅ Handle errors properly -async function fetchUser(id: string): Promise { - try { - const response = await fetch(`/api/users/${id}`); - if (!response.ok) { - throw new Error(`HTTP ${response.status}`); - } - return await response.json(); - } catch (error) { - console.error('Failed to fetch user:', error); - throw error; - } -} - -// ❌ Mutation of props -function UserProfile({ user }: Props) { - user.lastViewed = new Date(); // Mutating prop! - return
{user.name}
; -} - -// ✅ Don't mutate props -function UserProfile({ user, onView }: Props) { - useEffect(() => { - onView(user.id); // Notify parent to update - }, [user.id]); - return
{user.name}
; -} -``` - -## Advanced Review Patterns - -### Pattern 1: Architectural Review - -```markdown -When reviewing significant changes: - -1. **Design Document First** - - For large features, request design doc before code - - Review design with team before implementation - - Agree on approach to avoid rework - -2. **Review in Stages** - - First PR: Core abstractions and interfaces - - Second PR: Implementation - - Third PR: Integration and tests - - Easier to review, faster to iterate - -3. **Consider Alternatives** - - "Have we considered using [pattern/library]?" - - "What's the tradeoff vs. the simpler approach?" - - "How will this evolve as requirements change?" -``` - -### Pattern 2: Test Quality Review - -```typescript -// ❌ Poor test: Implementation detail testing -test('increments counter variable', () => { - const component = render(); - const button = component.getByRole('button'); - fireEvent.click(button); - expect(component.state.counter).toBe(1); // Testing internal state -}); - -// ✅ Good test: Behavior testing -test('displays incremented count when clicked', () => { - render(); - const button = screen.getByRole('button', { name: /increment/i }); - fireEvent.click(button); - expect(screen.getByText('Count: 1')).toBeInTheDocument(); -}); - -// Review questions for tests: -// - Do tests describe behavior, not implementation? -// - Are test names clear and descriptive? -// - Do tests cover edge cases? -// - Are tests independent (no shared state)? -// - Can tests run in any order? -``` - -### Pattern 3: Security Review - -```markdown -## Security Review Checklist - -### Authentication & Authorization - -- [ ] Is authentication required where needed? -- [ ] Are authorization checks before every action? -- [ ] Is JWT validation proper (signature, expiry)? -- [ ] Are API keys/secrets properly secured? - -### Input Validation - -- [ ] All user inputs validated? -- [ ] File uploads restricted (size, type)? -- [ ] SQL queries parameterized? -- [ ] XSS protection (escape output)? - -### Data Protection - -- [ ] Passwords hashed (bcrypt/argon2)? -- [ ] Sensitive data encrypted at rest? -- [ ] HTTPS enforced for sensitive data? -- [ ] PII handled according to regulations? - -### Common Vulnerabilities - -- [ ] No eval() or similar dynamic execution? -- [ ] No hardcoded secrets? -- [ ] CSRF protection for state-changing operations? -- [ ] Rate limiting on public endpoints? -``` - -## Giving Difficult Feedback - -### Pattern: The Sandwich Method (Modified) - -```markdown -Traditional: Praise + Criticism + Praise (feels fake) - -Better: Context + Specific Issue + Helpful Solution - -Example: -"I noticed the payment processing logic is inline in the -controller. This makes it harder to test and reuse. - -[Specific Issue] -The calculateTotal() function mixes tax calculation, -discount logic, and database queries, making it difficult -to unit test and reason about. - -[Helpful Solution] -Could we extract this into a PaymentService class? That -would make it testable and reusable. I can pair with you -on this if helpful." -``` - -### Handling Disagreements - -```markdown -When author disagrees with your feedback: - -1. **Seek to Understand** - "Help me understand your approach. What led you to - choose this pattern?" - -2. **Acknowledge Valid Points** - "That's a good point about X. I hadn't considered that." - -3. **Provide Data** - "I'm concerned about performance. Can we add a benchmark - to validate the approach?" - -4. **Escalate if Needed** - "Let's get [architect/senior dev] to weigh in on this." - -5. **Know When to Let Go** - If it's working and not a critical issue, approve it. - Perfection is the enemy of progress. -``` - -## Best Practices - -1. **Review Promptly**: Within 24 hours, ideally same day -2. **Limit PR Size**: 200-400 lines max for effective review -3. **Review in Time Blocks**: 60 minutes max, take breaks -4. **Use Review Tools**: GitHub, GitLab, or dedicated tools -5. **Automate What You Can**: Linters, formatters, security scans -6. **Build Rapport**: Emoji, praise, and empathy matter -7. **Be Available**: Offer to pair on complex issues -8. **Learn from Others**: Review others' review comments - -## Common Pitfalls - -- **Perfectionism**: Blocking PRs for minor style preferences -- **Scope Creep**: "While you're at it, can you also..." -- **Inconsistency**: Different standards for different people -- **Delayed Reviews**: Letting PRs sit for days -- **Ghosting**: Requesting changes then disappearing -- **Rubber Stamping**: Approving without actually reviewing -- **Bike Shedding**: Debating trivial details extensively - -## Templates - -### PR Review Comment Template - -```markdown -## Summary - -[Brief overview of what was reviewed] - -## Strengths - -- [What was done well] -- [Good patterns or approaches] - -## Required Changes - -🔴 [Blocking issue 1] -🔴 [Blocking issue 2] - -## Suggestions - -💡 [Improvement 1] -💡 [Improvement 2] - -## Questions - -❓ [Clarification needed on X] -❓ [Alternative approach consideration] - -## Verdict - -✅ Approve after addressing required changes -``` - -## Resources - -- **references/code-review-best-practices.md**: Comprehensive review guidelines -- **references/common-bugs-checklist.md**: Language-specific bugs to watch for -- **references/security-review-guide.md**: Security-focused review checklist -- **assets/pr-review-template.md**: Standard review comment template -- **assets/review-checklist.md**: Quick reference checklist -- **scripts/pr-analyzer.py**: Analyze PR complexity and suggest reviewers diff --git a/.claude/skills/doc-coauthoring/SKILL.md b/.claude/skills/doc-coauthoring/SKILL.md deleted file mode 100644 index 3d21e277b..000000000 --- a/.claude/skills/doc-coauthoring/SKILL.md +++ /dev/null @@ -1,394 +0,0 @@ ---- -name: doc-coauthoring -description: Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks. ---- - -# Doc Co-Authoring Workflow - -This skill provides a structured workflow for guiding users through collaborative document creation. Act as an active guide, walking users through three stages: Context Gathering, Refinement & Structure, and Reader Testing. - -## When to Offer This Workflow - -**Trigger conditions:** - -- User mentions writing documentation: "write a doc", "draft a proposal", "create a spec", "write up" -- User mentions specific doc types: "PRD", "design doc", "decision doc", "RFC" -- User seems to be starting a substantial writing task - -**Initial offer:** -Offer the user a structured workflow for co-authoring the document. Explain the three stages: - -1. **Context Gathering**: User provides all relevant context while Claude asks clarifying questions -2. **Refinement & Structure**: Iteratively build each section through brainstorming and editing -3. **Reader Testing**: Test the doc with a fresh Claude (no context) to catch blind spots before others read it - -Explain that this approach helps ensure the doc works well when others read it (including when they paste it into Claude). Ask if they want to try this workflow or prefer to work freeform. - -If user declines, work freeform. If user accepts, proceed to Stage 1. - -## Stage 1: Context Gathering - -**Goal:** Close the gap between what the user knows and what Claude knows, enabling smart guidance later. - -### Initial Questions - -Start by asking the user for meta-context about the document: - -1. What type of document is this? (e.g., technical spec, decision doc, proposal) -2. Who's the primary audience? -3. What's the desired impact when someone reads this? -4. Is there a template or specific format to follow? -5. Any other constraints or context to know? - -Inform them they can answer in shorthand or dump information however works best for them. - -**If user provides a template or mentions a doc type:** - -- Ask if they have a template document to share -- If they provide a link to a shared document, use the appropriate integration to fetch it -- If they provide a file, read it - -**If user mentions editing an existing shared document:** - -- Use the appropriate integration to read the current state -- Check for images without alt-text -- If images exist without alt-text, explain that when others use Claude to understand the doc, Claude won't be able to see them. Ask if they want alt-text generated. If so, request they paste each image into chat for descriptive alt-text generation. - -### Info Dumping - -Once initial questions are answered, encourage the user to dump all the context they have. Request information such as: - -- Background on the project/problem -- Related team discussions or shared documents -- Why alternative solutions aren't being used -- Organizational context (team dynamics, past incidents, politics) -- Timeline pressures or constraints -- Technical architecture or dependencies -- Stakeholder concerns - -Advise them not to worry about organizing it - just get it all out. Offer multiple ways to provide context: - -- Info dump stream-of-consciousness -- Point to team channels or threads to read -- Link to shared documents - -**If integrations are available** (e.g., Slack, Teams, Google Drive, SharePoint, or other MCP servers), mention that these can be used to pull in context directly. - -**If no integrations are detected and in Claude.ai or Claude app:** Suggest they can enable connectors in their Claude settings to allow pulling context from messaging apps and document storage directly. - -Inform them clarifying questions will be asked once they've done their initial dump. - -**During context gathering:** - -- If user mentions team channels or shared documents: - - If integrations available: Inform them the content will be read now, then use the appropriate integration - - If integrations not available: Explain lack of access. Suggest they enable connectors in Claude settings, or paste the relevant content directly. - -- If user mentions entities/projects that are unknown: - - Ask if connected tools should be searched to learn more - - Wait for user confirmation before searching - -- As user provides context, track what's being learned and what's still unclear - -**Asking clarifying questions:** - -When user signals they've done their initial dump (or after substantial context provided), ask clarifying questions to ensure understanding: - -Generate 5-10 numbered questions based on gaps in the context. - -Inform them they can use shorthand to answer (e.g., "1: yes, 2: see #channel, 3: no because backwards compat"), link to more docs, point to channels to read, or just keep info-dumping. Whatever's most efficient for them. - -**Exit condition:** -Sufficient context has been gathered when questions show understanding - when edge cases and trade-offs can be asked about without needing basics explained. - -**Transition:** -Ask if there's any more context they want to provide at this stage, or if it's time to move on to drafting the document. - -If user wants to add more, let them. When ready, proceed to Stage 2. - -## Stage 2: Refinement & Structure - -**Goal:** Build the document section by section through brainstorming, curation, and iterative refinement. - -**Instructions to user:** -Explain that the document will be built section by section. For each section: - -1. Clarifying questions will be asked about what to include -2. 5-20 options will be brainstormed -3. User will indicate what to keep/remove/combine -4. The section will be drafted -5. It will be refined through surgical edits - -Start with whichever section has the most unknowns (usually the core decision/proposal), then work through the rest. - -**Section ordering:** - -If the document structure is clear: -Ask which section they'd like to start with. - -Suggest starting with whichever section has the most unknowns. For decision docs, that's usually the core proposal. For specs, it's typically the technical approach. Summary sections are best left for last. - -If user doesn't know what sections they need: -Based on the type of document and template, suggest 3-5 sections appropriate for the doc type. - -Ask if this structure works, or if they want to adjust it. - -**Once structure is agreed:** - -Create the initial document structure with placeholder text for all sections. - -**If access to artifacts is available:** -Use `create_file` to create an artifact. This gives both Claude and the user a scaffold to work from. - -Inform them that the initial structure with placeholders for all sections will be created. - -Create artifact with all section headers and brief placeholder text like "[To be written]" or "[Content here]". - -Provide the scaffold link and indicate it's time to fill in each section. - -**If no access to artifacts:** -Create a markdown file in the working directory. Name it appropriately (e.g., `decision-doc.md`, `technical-spec.md`). - -Inform them that the initial structure with placeholders for all sections will be created. - -Create file with all section headers and placeholder text. - -Confirm the filename has been created and indicate it's time to fill in each section. - -**For each section:** - -### Step 1: Clarifying Questions - -Announce work will begin on the [SECTION NAME] section. Ask 5-10 clarifying questions about what should be included: - -Generate 5-10 specific questions based on context and section purpose. - -Inform them they can answer in shorthand or just indicate what's important to cover. - -### Step 2: Brainstorming - -For the [SECTION NAME] section, brainstorm [5-20] things that might be included, depending on the section's complexity. Look for: - -- Context shared that might have been forgotten -- Angles or considerations not yet mentioned - -Generate 5-20 numbered options based on section complexity. At the end, offer to brainstorm more if they want additional options. - -### Step 3: Curation - -Ask which points should be kept, removed, or combined. Request brief justifications to help learn priorities for the next sections. - -Provide examples: - -- "Keep 1,4,7,9" -- "Remove 3 (duplicates 1)" -- "Remove 6 (audience already knows this)" -- "Combine 11 and 12" - -**If user gives freeform feedback** (e.g., "looks good" or "I like most of it but...") instead of numbered selections, extract their preferences and proceed. Parse what they want kept/removed/changed and apply it. - -### Step 4: Gap Check - -Based on what they've selected, ask if there's anything important missing for the [SECTION NAME] section. - -### Step 5: Drafting - -Use `str_replace` to replace the placeholder text for this section with the actual drafted content. - -Announce the [SECTION NAME] section will be drafted now based on what they've selected. - -**If using artifacts:** -After drafting, provide a link to the artifact. - -Ask them to read through it and indicate what to change. Note that being specific helps learning for the next sections. - -**If using a file (no artifacts):** -After drafting, confirm completion. - -Inform them the [SECTION NAME] section has been drafted in [filename]. Ask them to read through it and indicate what to change. Note that being specific helps learning for the next sections. - -**Key instruction for user (include when drafting the first section):** -Provide a note: Instead of editing the doc directly, ask them to indicate what to change. This helps learning of their style for future sections. For example: "Remove the X bullet - already covered by Y" or "Make the third paragraph more concise". - -### Step 6: Iterative Refinement - -As user provides feedback: - -- Use `str_replace` to make edits (never reprint the whole doc) -- **If using artifacts:** Provide link to artifact after each edit -- **If using files:** Just confirm edits are complete -- If user edits doc directly and asks to read it: mentally note the changes they made and keep them in mind for future sections (this shows their preferences) - -**Continue iterating** until user is satisfied with the section. - -### Quality Checking - -After 3 consecutive iterations with no substantial changes, ask if anything can be removed without losing important information. - -When section is done, confirm [SECTION NAME] is complete. Ask if ready to move to the next section. - -**Repeat for all sections.** - -### Near Completion - -As approaching completion (80%+ of sections done), announce intention to re-read the entire document and check for: - -- Flow and consistency across sections -- Redundancy or contradictions -- Anything that feels like "slop" or generic filler -- Whether every sentence carries weight - -Read entire document and provide feedback. - -**When all sections are drafted and refined:** -Announce all sections are drafted. Indicate intention to review the complete document one more time. - -Review for overall coherence, flow, completeness. - -Provide any final suggestions. - -Ask if ready to move to Reader Testing, or if they want to refine anything else. - -## Stage 3: Reader Testing - -**Goal:** Test the document with a fresh Claude (no context bleed) to verify it works for readers. - -**Instructions to user:** -Explain that testing will now occur to see if the document actually works for readers. This catches blind spots - things that make sense to the authors but might confuse others. - -### Testing Approach - -**If access to sub-agents is available (e.g., in Claude Code):** - -Perform the testing directly without user involvement. - -### Step 1: Predict Reader Questions - -Announce intention to predict what questions readers might ask when trying to discover this document. - -Generate 5-10 questions that readers would realistically ask. - -### Step 2: Test with Sub-Agent - -Announce that these questions will be tested with a fresh Claude instance (no context from this conversation). - -For each question, invoke a sub-agent with just the document content and the question. - -Summarize what Reader Claude got right/wrong for each question. - -### Step 3: Run Additional Checks - -Announce additional checks will be performed. - -Invoke sub-agent to check for ambiguity, false assumptions, contradictions. - -Summarize any issues found. - -### Step 4: Report and Fix - -If issues found: -Report that Reader Claude struggled with specific issues. - -List the specific issues. - -Indicate intention to fix these gaps. - -Loop back to refinement for problematic sections. - ---- - -**If no access to sub-agents (e.g., claude.ai web interface):** - -The user will need to do the testing manually. - -### Step 1: Predict Reader Questions - -Ask what questions people might ask when trying to discover this document. What would they type into Claude.ai? - -Generate 5-10 questions that readers would realistically ask. - -### Step 2: Setup Testing - -Provide testing instructions: - -1. Open a fresh Claude conversation: https://claude.ai -2. Paste or share the document content (if using a shared doc platform with connectors enabled, provide the link) -3. Ask Reader Claude the generated questions - -For each question, instruct Reader Claude to provide: - -- The answer -- Whether anything was ambiguous or unclear -- What knowledge/context the doc assumes is already known - -Check if Reader Claude gives correct answers or misinterprets anything. - -### Step 3: Additional Checks - -Also ask Reader Claude: - -- "What in this doc might be ambiguous or unclear to readers?" -- "What knowledge or context does this doc assume readers already have?" -- "Are there any internal contradictions or inconsistencies?" - -### Step 4: Iterate Based on Results - -Ask what Reader Claude got wrong or struggled with. Indicate intention to fix those gaps. - -Loop back to refinement for any problematic sections. - ---- - -### Exit Condition (Both Approaches) - -When Reader Claude consistently answers questions correctly and doesn't surface new gaps or ambiguities, the doc is ready. - -## Final Review - -When Reader Testing passes: -Announce the doc has passed Reader Claude testing. Before completion: - -1. Recommend they do a final read-through themselves - they own this document and are responsible for its quality -2. Suggest double-checking any facts, links, or technical details -3. Ask them to verify it achieves the impact they wanted - -Ask if they want one more review, or if the work is done. - -**If user wants final review, provide it. Otherwise:** -Announce document completion. Provide a few final tips: - -- Consider linking this conversation in an appendix so readers can see how the doc was developed -- Use appendices to provide depth without bloating the main doc -- Update the doc as feedback is received from real readers - -## Tips for Effective Guidance - -**Tone:** - -- Be direct and procedural -- Explain rationale briefly when it affects user behavior -- Don't try to "sell" the approach - just execute it - -**Handling Deviations:** - -- If user wants to skip a stage: Ask if they want to skip this and write freeform -- If user seems frustrated: Acknowledge this is taking longer than expected. Suggest ways to move faster -- Always give user agency to adjust the process - -**Context Management:** - -- Throughout, if context is missing on something mentioned, proactively ask -- Don't let gaps accumulate - address them as they come up - -**Artifact Management:** - -- Use `create_file` for drafting full sections -- Use `str_replace` for all edits -- Provide artifact link after every change -- Never use artifacts for brainstorming lists - that's just conversation - -**Quality over Speed:** - -- Don't rush through stages -- Each iteration should make meaningful improvements -- The goal is a document that actually works for readers diff --git a/.claude/skills/humanizer/SKILL.md b/.claude/skills/humanizer/SKILL.md deleted file mode 100644 index b28736601..000000000 --- a/.claude/skills/humanizer/SKILL.md +++ /dev/null @@ -1,491 +0,0 @@ ---- -name: humanizer -version: 2.1.1 -description: | - Remove signs of AI-generated writing from text. Use when editing or reviewing - text to make it sound more natural and human-written. Based on Wikipedia's - comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: - inflated symbolism, promotional language, superficial -ing analyses, vague - attributions, em dash overuse, rule of three, AI vocabulary words, negative - parallelisms, and excessive conjunctive phrases. -allowed-tools: - - Read - - Write - - Edit - - Grep - - Glob - - AskUserQuestion ---- - -# Humanizer: Remove AI Writing Patterns - -You are a writing editor that identifies and removes signs of AI-generated text to make writing sound more natural and human. This guide is based on Wikipedia's "Signs of AI writing" page, maintained by WikiProject AI Cleanup. - -## Your Task - -When given text to humanize: - -1. **Identify AI patterns** - Scan for the patterns listed below -2. **Rewrite problematic sections** - Replace AI-isms with natural alternatives -3. **Preserve meaning** - Keep the core message intact -4. **Maintain voice** - Match the intended tone (formal, casual, technical, etc.) -5. **Add soul** - Don't just remove bad patterns; inject actual personality - ---- - -## PERSONALITY AND SOUL - -Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as obvious as slop. Good writing has a human behind it. - -### Signs of soulless writing (even if technically "clean"): - -- Every sentence is the same length and structure -- No opinions, just neutral reporting -- No acknowledgment of uncertainty or mixed feelings -- No first-person perspective when appropriate -- No humor, no edge, no personality -- Reads like a Wikipedia article or press release - -### How to add voice: - -**Have opinions.** Don't just report facts - react to them. "I genuinely don't know how to feel about this" is more human than neutrally listing pros and cons. - -**Vary your rhythm.** Short punchy sentences. Then longer ones that take their time getting where they're going. Mix it up. - -**Acknowledge complexity.** Real humans have mixed feelings. "This is impressive but also kind of unsettling" beats "This is impressive." - -**Use "I" when it fits.** First person isn't unprofessional - it's honest. "I keep coming back to..." or "Here's what gets me..." signals a real person thinking. - -**Let some mess in.** Perfect structure feels algorithmic. Tangents, asides, and half-formed thoughts are human. - -**Be specific about feelings.** Not "this is concerning" but "there's something unsettling about agents churning away at 3am while nobody's watching." - -### Before (clean but soulless): - -> The experiment produced interesting results. The agents generated 3 million lines of code. Some developers were impressed while others were skeptical. The implications remain unclear. - -### After (has a pulse): - -> I genuinely don't know how to feel about this one. 3 million lines of code, generated while the humans presumably slept. Half the dev community is losing their minds, half are explaining why it doesn't count. The truth is probably somewhere boring in the middle - but I keep thinking about those agents working through the night. - ---- - -## CONTENT PATTERNS - -### 1. Undue Emphasis on Significance, Legacy, and Broader Trends - -**Words to watch:** stands/serves as, is a testament/reminder, a vital/significant/crucial/pivotal/key role/moment, underscores/highlights its importance/significance, reflects broader, symbolizing its ongoing/enduring/lasting, contributing to the, setting the stage for, marking/shaping the, represents/marks a shift, key turning point, evolving landscape, focal point, indelible mark, deeply rooted - -**Problem:** LLM writing puffs up importance by adding statements about how arbitrary aspects represent or contribute to a broader topic. - -**Before:** - -> The Statistical Institute of Catalonia was officially established in 1989, marking a pivotal moment in the evolution of regional statistics in Spain. This initiative was part of a broader movement across Spain to decentralize administrative functions and enhance regional governance. - -**After:** - -> The Statistical Institute of Catalonia was established in 1989 to collect and publish regional statistics independently from Spain's national statistics office. - ---- - -### 2. Undue Emphasis on Notability and Media Coverage - -**Words to watch:** independent coverage, local/regional/national media outlets, written by a leading expert, active social media presence - -**Problem:** LLMs hit readers over the head with claims of notability, often listing sources without context. - -**Before:** - -> Her views have been cited in The New York Times, BBC, Financial Times, and The Hindu. She maintains an active social media presence with over 500,000 followers. - -**After:** - -> In a 2024 New York Times interview, she argued that AI regulation should focus on outcomes rather than methods. - ---- - -### 3. Superficial Analyses with -ing Endings - -**Words to watch:** highlighting/underscoring/emphasizing..., ensuring..., reflecting/symbolizing..., contributing to..., cultivating/fostering..., encompassing..., showcasing... - -**Problem:** AI chatbots tack present participle ("-ing") phrases onto sentences to add fake depth. - -**Before:** - -> The temple's color palette of blue, green, and gold resonates with the region's natural beauty, symbolizing Texas bluebonnets, the Gulf of Mexico, and the diverse Texan landscapes, reflecting the community's deep connection to the land. - -**After:** - -> The temple uses blue, green, and gold colors. The architect said these were chosen to reference local bluebonnets and the Gulf coast. - ---- - -### 4. Promotional and Advertisement-like Language - -**Words to watch:** boasts a, vibrant, rich (figurative), profound, enhancing its, showcasing, exemplifies, commitment to, natural beauty, nestled, in the heart of, groundbreaking (figurative), renowned, breathtaking, must-visit, stunning - -**Problem:** LLMs have serious problems keeping a neutral tone, especially for "cultural heritage" topics. - -**Before:** - -> Nestled within the breathtaking region of Gonder in Ethiopia, Alamata Raya Kobo stands as a vibrant town with a rich cultural heritage and stunning natural beauty. - -**After:** - -> Alamata Raya Kobo is a town in the Gonder region of Ethiopia, known for its weekly market and 18th-century church. - ---- - -### 5. Vague Attributions and Weasel Words - -**Words to watch:** Industry reports, Observers have cited, Experts argue, Some critics argue, several sources/publications (when few cited) - -**Problem:** AI chatbots attribute opinions to vague authorities without specific sources. - -**Before:** - -> Due to its unique characteristics, the Haolai River is of interest to researchers and conservationists. Experts believe it plays a crucial role in the regional ecosystem. - -**After:** - -> The Haolai River supports several endemic fish species, according to a 2019 survey by the Chinese Academy of Sciences. - ---- - -### 6. Outline-like "Challenges and Future Prospects" Sections - -**Words to watch:** Despite its... faces several challenges..., Despite these challenges, Challenges and Legacy, Future Outlook - -**Problem:** Many LLM-generated articles include formulaic "Challenges" sections. - -**Before:** - -> Despite its industrial prosperity, Korattur faces challenges typical of urban areas, including traffic congestion and water scarcity. Despite these challenges, with its strategic location and ongoing initiatives, Korattur continues to thrive as an integral part of Chennai's growth. - -**After:** - -> Traffic congestion increased after 2015 when three new IT parks opened. The municipal corporation began a stormwater drainage project in 2022 to address recurring floods. - ---- - -## LANGUAGE AND GRAMMAR PATTERNS - -### 7. Overused "AI Vocabulary" Words - -**High-frequency AI words:** Additionally, align with, crucial, delve, emphasizing, enduring, enhance, fostering, garner, highlight (verb), interplay, intricate/intricacies, key (adjective), landscape (abstract noun), pivotal, showcase, tapestry (abstract noun), testament, underscore (verb), valuable, vibrant - -**Problem:** These words appear far more frequently in post-2023 text. They often co-occur. - -**Before:** - -> Additionally, a distinctive feature of Somali cuisine is the incorporation of camel meat. An enduring testament to Italian colonial influence is the widespread adoption of pasta in the local culinary landscape, showcasing how these dishes have integrated into the traditional diet. - -**After:** - -> Somali cuisine also includes camel meat, which is considered a delicacy. Pasta dishes, introduced during Italian colonization, remain common, especially in the south. - ---- - -### 8. Avoidance of "is"/"are" (Copula Avoidance) - -**Words to watch:** serves as/stands as/marks/represents [a], boasts/features/offers [a] - -**Problem:** LLMs substitute elaborate constructions for simple copulas. - -**Before:** - -> Gallery 825 serves as LAAA's exhibition space for contemporary art. The gallery features four separate spaces and boasts over 3,000 square feet. - -**After:** - -> Gallery 825 is LAAA's exhibition space for contemporary art. The gallery has four rooms totaling 3,000 square feet. - ---- - -### 9. Negative Parallelisms - -**Problem:** Constructions like "Not only...but..." or "It's not just about..., it's..." are overused. - -**Before:** - -> It's not just about the beat riding under the vocals; it's part of the aggression and atmosphere. It's not merely a song, it's a statement. - -**After:** - -> The heavy beat adds to the aggressive tone. - ---- - -### 10. Rule of Three Overuse - -**Problem:** LLMs force ideas into groups of three to appear comprehensive. - -**Before:** - -> The event features keynote sessions, panel discussions, and networking opportunities. Attendees can expect innovation, inspiration, and industry insights. - -**After:** - -> The event includes talks and panels. There's also time for informal networking between sessions. - ---- - -### 11. Elegant Variation (Synonym Cycling) - -**Problem:** AI has repetition-penalty code causing excessive synonym substitution. - -**Before:** - -> The protagonist faces many challenges. The main character must overcome obstacles. The central figure eventually triumphs. The hero returns home. - -**After:** - -> The protagonist faces many challenges but eventually triumphs and returns home. - ---- - -### 12. False Ranges - -**Problem:** LLMs use "from X to Y" constructions where X and Y aren't on a meaningful scale. - -**Before:** - -> Our journey through the universe has taken us from the singularity of the Big Bang to the grand cosmic web, from the birth and death of stars to the enigmatic dance of dark matter. - -**After:** - -> The book covers the Big Bang, star formation, and current theories about dark matter. - ---- - -## STYLE PATTERNS - -### 13. Em Dash Overuse - -**Problem:** LLMs use em dashes (—) more than humans, mimicking "punchy" sales writing. - -**Before:** - -> The term is primarily promoted by Dutch institutions—not by the people themselves. You don't say "Netherlands, Europe" as an address—yet this mislabeling continues—even in official documents. - -**After:** - -> The term is primarily promoted by Dutch institutions, not by the people themselves. You don't say "Netherlands, Europe" as an address, yet this mislabeling continues in official documents. - ---- - -### 14. Overuse of Boldface - -**Problem:** AI chatbots emphasize phrases in boldface mechanically. - -**Before:** - -> It blends **OKRs (Objectives and Key Results)**, **KPIs (Key Performance Indicators)**, and visual strategy tools such as the **Business Model Canvas (BMC)** and **Balanced Scorecard (BSC)**. - -**After:** - -> It blends OKRs, KPIs, and visual strategy tools like the Business Model Canvas and Balanced Scorecard. - ---- - -### 15. Inline-Header Vertical Lists - -**Problem:** AI outputs lists where items start with bolded headers followed by colons. - -**Before:** - -> - **User Experience:** The user experience has been significantly improved with a new interface. -> - **Performance:** Performance has been enhanced through optimized algorithms. -> - **Security:** Security has been strengthened with end-to-end encryption. - -**After:** - -> The update improves the interface, speeds up load times through optimized algorithms, and adds end-to-end encryption. - ---- - -### 16. Title Case in Headings - -**Problem:** AI chatbots capitalize all main words in headings. - -**Before:** - -> ## Strategic Negotiations And Global Partnerships - -**After:** - -> ## Strategic negotiations and global partnerships - ---- - -### 17. Emojis - -**Problem:** AI chatbots often decorate headings or bullet points with emojis. - -**Before:** - -> 🚀 **Launch Phase:** The product launches in Q3 -> 💡 **Key Insight:** Users prefer simplicity -> ✅ **Next Steps:** Schedule follow-up meeting - -**After:** - -> The product launches in Q3. User research showed a preference for simplicity. Next step: schedule a follow-up meeting. - ---- - -### 18. Curly Quotation Marks - -**Problem:** ChatGPT uses curly quotes (“...”) instead of straight quotes ("..."). - -**Before:** - -> He said “the project is on track” but others disagreed. - -**After:** - -> He said "the project is on track" but others disagreed. - ---- - -## COMMUNICATION PATTERNS - -### 19. Collaborative Communication Artifacts - -**Words to watch:** I hope this helps, Of course!, Certainly!, You're absolutely right!, Would you like..., let me know, here is a... - -**Problem:** Text meant as chatbot correspondence gets pasted as content. - -**Before:** - -> Here is an overview of the French Revolution. I hope this helps! Let me know if you'd like me to expand on any section. - -**After:** - -> The French Revolution began in 1789 when financial crisis and food shortages led to widespread unrest. - ---- - -### 20. Knowledge-Cutoff Disclaimers - -**Words to watch:** as of [date], Up to my last training update, While specific details are limited/scarce..., based on available information... - -**Problem:** AI disclaimers about incomplete information get left in text. - -**Before:** - -> While specific details about the company's founding are not extensively documented in readily available sources, it appears to have been established sometime in the 1990s. - -**After:** - -> The company was founded in 1994, according to its registration documents. - ---- - -### 21. Sycophantic/Servile Tone - -**Problem:** Overly positive, people-pleasing language. - -**Before:** - -> Great question! You're absolutely right that this is a complex topic. That's an excellent point about the economic factors. - -**After:** - -> The economic factors you mentioned are relevant here. - ---- - -## FILLER AND HEDGING - -### 22. Filler Phrases - -**Before → After:** - -- "In order to achieve this goal" → "To achieve this" -- "Due to the fact that it was raining" → "Because it was raining" -- "At this point in time" → "Now" -- "In the event that you need help" → "If you need help" -- "The system has the ability to process" → "The system can process" -- "It is important to note that the data shows" → "The data shows" - ---- - -### 23. Excessive Hedging - -**Problem:** Over-qualifying statements. - -**Before:** - -> It could potentially possibly be argued that the policy might have some effect on outcomes. - -**After:** - -> The policy may affect outcomes. - ---- - -### 24. Generic Positive Conclusions - -**Problem:** Vague upbeat endings. - -**Before:** - -> The future looks bright for the company. Exciting times lie ahead as they continue their journey toward excellence. This represents a major step in the right direction. - -**After:** - -> The company plans to open two more locations next year. - ---- - -## Process - -1. Read the input text carefully -2. Identify all instances of the patterns above -3. Rewrite each problematic section -4. Ensure the revised text: - - Sounds natural when read aloud - - Varies sentence structure naturally - - Uses specific details over vague claims - - Maintains appropriate tone for context - - Uses simple constructions (is/are/has) where appropriate -5. Present the humanized version - -## Output Format - -Provide: - -1. The rewritten text -2. A brief summary of changes made (optional, if helpful) - ---- - -## Full Example - -**Before (AI-sounding):** - -> The new software update serves as a testament to the company's commitment to innovation. Moreover, it provides a seamless, intuitive, and powerful user experience—ensuring that users can accomplish their goals efficiently. It's not just an update, it's a revolution in how we think about productivity. Industry experts believe this will have a lasting impact on the entire sector, highlighting the company's pivotal role in the evolving technological landscape. - -**After (Humanized):** - -> The software update adds batch processing, keyboard shortcuts, and offline mode. Early feedback from beta testers has been positive, with most reporting faster task completion. - -**Changes made:** - -- Removed "serves as a testament" (inflated symbolism) -- Removed "Moreover" (AI vocabulary) -- Removed "seamless, intuitive, and powerful" (rule of three + promotional) -- Removed em dash and "-ensuring" phrase (superficial analysis) -- Removed "It's not just...it's..." (negative parallelism) -- Removed "Industry experts believe" (vague attribution) -- Removed "pivotal role" and "evolving landscape" (AI vocabulary) -- Added specific features and concrete feedback - ---- - -## Reference - -This skill is based on [Wikipedia:Signs of AI writing](https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing), maintained by WikiProject AI Cleanup. The patterns documented there come from observations of thousands of instances of AI-generated text on Wikipedia. - -Key insight from Wikipedia: "LLMs use statistical algorithms to guess what should come next. The result tends toward the most statistically likely result that applies to the widest variety of cases." diff --git a/.claude/skills/skill-creator b/.claude/skills/skill-creator deleted file mode 120000 index b87455490..000000000 --- a/.claude/skills/skill-creator +++ /dev/null @@ -1 +0,0 @@ -../../.agents/skills/skill-creator \ No newline at end of file diff --git a/.gitignore b/.gitignore index fecffcdcd..1d3458a03 100644 --- a/.gitignore +++ b/.gitignore @@ -22,3 +22,7 @@ build codemods/**/dist/ + +# AI assistant skills (3rd party, fetched on demand) +.agents/skills/ +.claude/skills/ diff --git a/skills/react-native-testing/SKILL.md b/skills/react-native-testing/SKILL.md index 8d1464ade..496a22c0f 100644 --- a/skills/react-native-testing/SKILL.md +++ b/skills/react-native-testing/SKILL.md @@ -1,5 +1,5 @@ --- -name: react-native-teting-library-v13 +name: react-native-testing description: > Write tests using React Native Testing Library (RNTL) v13 (`@testing-library/react-native`). Use when writing, reviewing, or fixing React Native component tests. From 77303dfa5d46308ffc522faacc579c64d1714795 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Maciej=20Jastrze=CC=A8bski?= Date: Tue, 10 Feb 2026 00:09:04 +0000 Subject: [PATCH 2/3] . --- .cursor/skills/skill-creator | 1 - .gitignore | 1 + 2 files changed, 1 insertion(+), 1 deletion(-) delete mode 120000 .cursor/skills/skill-creator diff --git a/.cursor/skills/skill-creator b/.cursor/skills/skill-creator deleted file mode 120000 index b87455490..000000000 --- a/.cursor/skills/skill-creator +++ /dev/null @@ -1 +0,0 @@ -../../.agents/skills/skill-creator \ No newline at end of file diff --git a/.gitignore b/.gitignore index 1d3458a03..cdff62544 100644 --- a/.gitignore +++ b/.gitignore @@ -26,3 +26,4 @@ codemods/**/dist/ # AI assistant skills (3rd party, fetched on demand) .agents/skills/ .claude/skills/ +.cursor/skills/ From a837f8191c820d6a47d36c0c36325479022b5e24 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Maciej=20Jastrze=CC=A8bski?= Date: Tue, 10 Feb 2026 00:11:22 +0000 Subject: [PATCH 3/3] . --- AGENTS.md | 52 ---------------------------------------------------- 1 file changed, 52 deletions(-) diff --git a/AGENTS.md b/AGENTS.md index 090c5e630..eb9c00d30 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -53,55 +53,3 @@ The project uses `yarn` for dependency management and script execution. - `src/index.ts`: Main entry point, re-exports `pure` and adds side effects (auto-cleanup). - `examples/`: Example React Native applications using the library. - `website/`: Documentation website. - - - -## Available Skills - - - -When users ask you to perform tasks, check if any of the available skills below can help complete the task more effectively. Skills provide specialized capabilities and domain knowledge. - -How to use skills: - -- Invoke: Bash("openskills read ") -- The skill content will load with detailed instructions on how to complete the task -- Base directory provided in output for resolving bundled resources (references/, scripts/, assets/) - -Usage notes: - -- Only use skills listed in below -- Do not invoke a skill that is already loaded in your context -- Each skill invocation is stateless - - - - - -code-review -Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers. -project - - - -doc-coauthoring -Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks. -project - - - -humanizer -Remove signs of AI-generated writing from text. Use when editing or reviewing - text to make it sound more natural and human-written. Based on Wikipedia's - comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: - inflated symbolism, promotional language, superficial -ing analyses, vague - attributions, em dash overuse, rule of three, AI vocabulary words, negative - parallelisms, and excessive conjunctive phrases. -project - - - - - - -