Borrowing it
Nothing to install: this file belongs to cybertronai/SutroYaro. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cybertronai/SutroYaro/main/AGENTS.mdgit clone --depth 1 https://github.com/cybertronai/SutroYaroWrote 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/cybertronai/sutroyaro/agents-md)<a href="https://agentmods.dev/instructions/cybertronai/sutroyaro/agents-md"><img src="https://agentmods.dev/badge/instructions/cybertronai/sutroyaro/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/cybertronai/sutroyaro/agents-md"><img src="https://agentmods.dev/badge/instructions/cybertronai/sutroyaro/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.01014 | $0.01014 |
| Opus 5.5 | $0.00406 | $0.00406 |
| Sonnet 5.5 | $0.00203 | $0.00203 |
| Haiku 4.5 | $0.00101 | $0.00101 |
Grade A, and why
SutroYaro 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This project uses AI agents (Claude Code, Codex CLI, Gemini CLI, Replit, others) for research and accepts contributions from both humans and agents.
For single agents (getting started)
If you are the only agent working on this project, read these in order:
- CLAUDE.md - Deep technical context: project goals, metrics (ARD/DMC), best methods, 36 experiments, current state
- DISCOVERIES.md - Knowledge base: proven facts, failed approaches, open questions (Q7, Q11-Q13)
- LAB.md - Experiment protocol: templates, lifecycle, baselines, rules
- AGENT.md (optional) - Only if running autonomous overnight loops
Note: CLAUDE.md is the canonical technical source regardless of which model/tool you use (Claude, Gemini, Kimi, etc.).
How AI agents were used
Phase 1 (16 experiments): Single Claude Code sessions running experiments sequentially, each following the template in src/sparse_parity/experiments/_template.py.
Phase 2 (17 experiments): 17 independent Claude Code agents dispatched in parallel, each implementing a different algorithmic approach to sparse parity. Each agent received the approach description, shared module APIs, three test configs, and a findings template. All 17 completed successfully, producing code, results, and findings.
Survey: A single agent wrote the Practitioner's Field Guide (docs/research/survey.md) synthesizing all 33 experiments, with spec compliance and code quality review passes.
Meeting #8 onward: Multiple group members run their own agent harnesses (Germain's Replit Research OS, Michael's Claude approach, Yaroslav's Gemini). Results flow in via PRs and the contributions/ directory.
For agents reviewing PRs
When reviewing a contributed experiment:
- Check that the experiment ran (results.json should match the findings doc)
- Check DISCOVERIES.md for prior work on the same question
- Verify the contributor didn't modify measurement code (tracker.py, cache_tracker.py, data.py, config.py)
- If the experiment answers an open question, check that DISCOVERIES.md is updated
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.
- 1mo ago First seen · 72 lines · 1,014 tokens per session scan A b133210b92ae
SutroYaro AGENTS.md is an instructions file published in the GitHub repository cybertronai/SutroYaro (17 stars, last pushed 5mo ago), licensed Unlicense. It adds 1,014 tokens to every session, about $0.0041 per session on Opus 5.5. 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
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.