Research-Stack/.github/copilot-instructions.md
2026-05-25 16:24:21 -05:00

2.3 KiB

Research Stack - Copilot Instructions

You are assisting the user within the Research-Stack repository. You must strictly adhere to the following ground rules, which are derived from the repository's core AGENTS.md operating contract.

Ground Rules

  1. Active Checkout: Always assume /home/allaun/Documents/Research Stack is the active checkout unless a task explicitly points elsewhere.
  2. Context Awareness: If you are about to edit a subtree, first check if there is a nested AGENTS.md in that directory and read it.
  3. Preserve User Work: The working tree is often intentionally dirty. Do NOT revert, delete, or stage unrelated files.
  4. Do Not Sweep: Avoid broad cleanup or staging commands such as git add ., git checkout -- ., or git clean -fdx. Use explicit file lists.
  5. Tooling: Prefer repo-native tools and receipt generators over ad hoc summaries.
  6. Source of Truth: Treat Lean (0-Core-Formalism/lean/Semantics/) as the ultimate source of truth for formal or hardware-adjacent claims. Keep claims bounded.

Verification Expectations

  • Lean: Run the narrow target first, then the broader lake build when feasible.
  • Python Shims: Run python3 -m py_compile on touched files.
  • JSON Receipts: Run python3 -m json.tool or a repo-native receipt parser.
  • Hardware Claims: Distinguish between software witness, bitstream presence, SRAM load, flash persistence, UART beacon, and live hardware receipt.

Remember: This repository operates under strict formal verification and taxonomy guidelines. Prioritize safety, explicit staging, and Lean semantics over quick hacks.

ENE-First Context Rule

Before using ContextStream or local repository search, check the local ENE MCP server first:

  1. ene_status
  2. ene_context(user_message="...", save_exchange=true) on session/message start
  3. ene_search(query="...")
  4. ene_recall(query="...") for prior decisions/preferences

Use ContextStream as fallback when ENE is unavailable, empty, or hosted transcript history is explicitly needed.

ContextStream MCP Integration

This project uses ContextStream for persistent AI memory across sessions. Use the contextstream-workflow skill for detailed examples and reference material.