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Introduce structured AI agent instructions following Intel's AGENTS spec v4: - AGENTS.md: project context (RNG interface, archetype, structure, source-of-truth) - .github/copilot-instructions.md: agent behavior policy Key guidance: - Preserve numpy.random API compatibility - RNG specifics: BRNG selection, statistical properties - Cython: release GIL for MKL RNG calls (thread-safe) - Local dev: conda env + pip install -e . - Statistical validation required for RNG changes Token budget: 217 words (AGENTS.md) + copilot-instructions Based on mkl_fft pattern
napetrov
requested review from
antonwolfy,
jharlow-intel,
ndgrigorian and
xaleryb
as code owners
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What
Add structured AI agent instructions following Intel's AGENTS spec v4:
AGENTS.md— project context for agents (RNG interface, archetype, structure, source-of-truth mapping).github/copilot-instructions.md— agent behavior policy (precedence, contribution expectations, Intel-specific constraints)Why
Standardizes how AI coding assistants (GitHub Copilot, Claude, etc.) understand and work with this repo, reducing hallucinations and enforcing Intel engineering standards automatically.
Key guidance added
numpy.randomAPI compatibility by defaultwith nogil:) for MKL RNG calls (thread-safe in MKL)__init__.pyconda create -n dev python numpy cython mkl-devel pytest && pip install -e .Token budget
AGENTS.md: 217 words (limit 220)Checklist