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/callstackincubator/evals/agents-mdgit clone --depth 1 https://github.com/callstackincubator/evalsWhat 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 | $0.01309 | $0.01309 |
| Opus 5 | $0.00655 | $0.00655 |
| Sonnet 5 | $0.00262 | $0.00262 |
| Haiku 4.5 | $0.00131 | $0.00131 |
Grade A, and why
evals 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.
How it starts
The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS Guide
This file is the practical playbook for agents working in this repo.
What this repo is
- Purpose: benchmark how coding models solve React Native tasks.
- Primary engine:
runner/orchestrates discovery -> solve -> LLM judge -> summary. - Dataset: evals under
evals/<category>/<eval-id>/, typically with:prompt.mdrequirements.yamlapp/(baseline input)reference/(reference output for judge context)
Mental model of execution
Benchmark execution uses two CLIs:
bun runner/run.tsdiscovers evals and generates artifacts under the configured output directory.bun runner/judge.tsreads generated artifacts, runs LLM judging, and writes results underresults/<run-id>/.
Generation details (runner/solver/pipeline.ts):
--modelis required and is always used for generation.
Judge details (runner/evaluators/llm/run.ts):
--modelis required and LLM judge always runs against generated artifacts.
Key output behavior:
- Per-eval results:
results/<run-id>/evals/<eval-id>.json - Summary:
results/<run-id>/summary.json --debugadds judge prompt/output artifacts.
Think-before-coding rules (required)
Apply these before implementation:
- State assumptions explicitly.
- If multiple interpretations exist, list them and ask or choose with justification.
- If a simpler approach works, use it and say why.
- If something is unclear, stop and surface the exact ambiguity.
Execution principles (default policy)
Before implementing
- State assumptions explicitly. If uncertain, ask.
- If multiple interpretations exist, present them; do not pick silently.
- If a simpler approach exists, call it out and use it unless there is a clear reason not to.
Simplicity and scope control
- Implement only what the task asks for.
- No speculative abstractions for single-use code.
- No drive-by refactors.
- Match surrounding style.
- Remove only dead code created by your own change.
- If you notice unrelated issues, mention them but do not fix unless asked.
- Remove imports/variables your changes made unused; do not clean pre-existing dead code unless requested.
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 · 137 lines · 1,309 tokens per session scan A 6f7611c3d54d
evals AGENTS.md is an instructions file published in the GitHub repository callstackincubator/evals (110 stars, last pushed 1mo ago), licensed MIT. It adds 1,309 tokens to every session, about $0.0065 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
mastra AGENTS.md
AGENTS.md instructions for mastra-ai/mastra: Unless asked, don't inspect reference or modify examples. Use the most-specific AGENTS.md; for package work, read packages/ /AGENTS.md first.
mastra CLAUDE.md
Claude Code instructions for mastra-ai/mastra, a project described as: Mastra is the modern TypeScript framework for AI-powered applications and agents.
cali AGENTS.md
Instructions for callstackincubator/cali, covering agents.md, first 60 seconds, repo shape, cali runtime shape and public commands.
prefect-mcp-server CLAUDE.md
Instructions for PrefectHQ/prefect-mcp-server, covering rules for contributors, investigating eval failures in ci, get check run id for the evaluation results, get annotations with failure details and fastmcp client.
brief-spec AGENTS.md
Instructions for luanmorenommaciel/brief-spec: Before any task, read OPERATING.md. Do not invent a second loop. Do not skip the HMAC seal. Do not put family hops in docs/.
tracelens CLAUDE.md
Instructions for ssf0409/tracelens, covering tracelens - development guide, project overview, ownership boundary, tracelens owns and downstream projects own.