Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/sandeep-alluru/rulegraph/copilot-instructionsgit clone --depth 1 https://github.com/sandeep-alluru/rulegraphWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/sandeep-alluru/rulegraph/copilot-instructions)<a href="https://agentmods.dev/instructions/sandeep-alluru/rulegraph/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/sandeep-alluru/rulegraph/copilot-instructions.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00243 | $0.00243 |
| Opus 5 | $0.00121 | $0.00121 |
| Sonnet 5 | $0.00049 | $0.00049 |
| Haiku 4.5 | $0.00024 | $0.00024 |
Grade A, and why
rulegraph copilot-instructions.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
81% identical to groundcrew copilot-instructions.md — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
GitHub Copilot Instructions — rulegraph
rulegraph: Natural-language rulebook compiler for game arbitration
Module map
src/rulegraph/
├── # TODO: fill in after implementation
Key invariants
- TODO: document invariants
Code style
- Python 3.10+, type-annotated, mypy strict mode
- Ruff lint rules: E W F I UP B S N SIM RUF PT; ignore S101 (assert in tests), N806
- No
print()in library code — userich.console.Console - All public classes and functions must have docstrings
- Tests use
pytest; CLI tests useclick.testing.CliRunner
Adding a new output format
- Add
to_<format>(result) -> strinreport.py - Add format name to
--formatchoices incli.py - Add tests
Adding a new adapter / integration
- Create
src/rulegraph/instrument_<framework>.py - Export from
__init__.py, add to__all__alphabetically - Add tests
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 35 lines · 243 tokens per session scan A 2e7cc7997c01
rulegraph copilot-instructions.md is an instructions file published in the GitHub repository sandeep-alluru/rulegraph (0 stars, last pushed 18d ago), licensed MIT. It adds 243 tokens to every session, about $0.0012 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to groundcrew copilot-instructions.md, differing in 8 lines, and is treated as a copy.
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