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/graycodeai/starling/agents-mdgit clone --depth 1 https://github.com/GrayCodeAI/starlingWhat 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 | $0.01073 | $0.01073 |
| Opus 5 | $0.00536 | $0.00536 |
| Sonnet 5 | $0.00215 | $0.00215 |
| Haiku 4.5 | $0.00107 | $0.00107 |
Grade A, and why
starling AGENTS.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 yesterday.
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
78% identical to tabularis AGENTS.md — 68 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.
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
starling Conventions
Community skill packages for hawk.
Development workflow
When starting any new work (feature, fix, refactor, chore), always create a feature branch from main first. Never commit directly to main. Use branch naming conventions like feat/<description>, fix/<description>, or chore/<description>. Open a PR, ensure CI is green, then merge.
Structure
categories/<category>/<skill-name>/
├── SKILL.md # Required
├── templates/ # Optional
├── examples/ # Optional
└── scripts/ # Optional
Validation
# Validate a single skill
python tools/validate_skill.py categories/python/mdc-fastapi/SKILL.md
# Update registry after adding/removing skills
python tools/update_registry.py
# Full test suite
pytest
# Lint
ruff check .
ruff format --check .
Ecosystem Boundaries
- Extends Hawk through public skill and plugin surfaces only
- Do not reference support engine repos (
eyrie,yaad,tok,trace,sight,inspect) - Do not reference
hawk/internal/*or removed legacy paths
For full hawk-eco extension guidelines, see hawk/AGENTS.md.
GitNexus — Code Intelligence
This project is indexed by GitNexus as starling (210621 symbols, 225507 relationships, 136 execution flows). Use the GitNexus MCP tools to understand code, assess impact, and navigate safely.
Index stale? Run
node .gitnexus/run.cjs analyzefrom the project root — it auto-selects an available runner. No.gitnexus/run.cjsyet?npx gitnexus analyze(npm 11 crash →npm i -g gitnexus; #1939).
Always Do
- MUST run impact analysis before editing any symbol. Before modifying a function, class, or method, run
impact({target: "symbolName", direction: "upstream"})and report the blast radius (direct callers, affected processes, risk level) to the user. - MUST run
detect_changes()before committing to verify your changes only affect expected symbols and execution flows. For regression review, compare against the default branch:detect_changes({scope: "compare", base_ref: "main"}). - MUST warn the user if impact analysis returns HIGH or CRITICAL risk before proceeding with edits.
- When exploring unfamiliar code, use
query({search_query: "concept"})to find execution flows instead of grepping. It returns process-grouped results ranked by relevance. - When you need full context on a specific symbol — callers, callees, which execution flows it participates in — use
context({name: "symbolName"}). - For security review,
explain({target: "fileOrSymbol"})lists taint findings (source→sink flows; needsanalyze --pdg).
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.
- yesterday First seen · 94 lines · 1,073 tokens per session scan A 4bdfd42b95a5
starling AGENTS.md is an instructions file published in the GitHub repository GrayCodeAI/starling (2 stars, last pushed 2d ago), licensed MIT. It adds 1,073 tokens to every session, about $0.0054 per session on Opus 5. A static security scan graded it A with 0 findings. It is 78% identical to tabularis AGENTS.md, differing in 68 lines, and is treated as a copy.
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docpull AGENTS.md
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