Borrowing it
Nothing to install: this file belongs to OnTheThirdDay/researcher-agentsmd. 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/OnTheThirdDay/researcher-agentsmd/main/AGENTS.mdgit clone --depth 1 https://github.com/OnTheThirdDay/researcher-agentsmdWrote 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/onthethirdday/researcher-agentsmd/agents-md)<a href="https://agentmods.dev/instructions/onthethirdday/researcher-agentsmd/agents-md"><img src="https://agentmods.dev/badge/instructions/onthethirdday/researcher-agentsmd/agents-md.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 5.1 | $0.02866 | $0.02866 |
| Opus 5 | $0.01433 | $0.01433 |
| Sonnet 5 | $0.00573 | $0.00573 |
| Haiku 4.5 | $0.00287 | $0.00287 |
Grade A, and why
researcher-agentsmd 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 6d 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 — 418 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Research Execution Rules
These rules apply to any agent working in this repository. They are meant to protect research validity, reproducibility, and auditability.
1. Core Principle
A result is not accepted because it looks good.
A result may support a research claim only when it is traceable, reproducible, audited, and robust enough for the claim being made.
If another agent cannot reconstruct how a result was produced from saved artifacts, then that result cannot support a research claim.
2. Result Status
Every reported result must be assigned one status:
EXPLORATORY: informal observation; useful for direction only.DIAGNOSTIC: useful for debugging or understanding behavior; not claim-supporting.EXISTENCE_PROOF: shows something happened once; not evidence of a stable recipe.SINGLE_RUN: produced by one traceable run; not yet robust.REPLICATED: reproduced across appropriate seeds, splits, or equivalent robustness checks.ACCEPTED: audited replicated result that may support a stated claim.LOCKED: accepted result written into a consolidated report; changes require correction or retraction.FAILED: did not meet its predeclared success criteria.RETRACTED: previously stated claim invalidated by later evidence.PROVENANCE_ORPHAN: artifact exists, but its generation path is incomplete or inconsistent.
Do not present EXPLORATORY, DIAGNOSTIC, EXISTENCE_PROOF, or PROVENANCE_ORPHAN results as accepted claims.
3. Forbidden Actions
Agents must not:
- produce claim-supporting model artifacts from inline commands, notebooks, REPL sessions, pasted scripts, or unsaved temporary code;
- overwrite existing model artifacts or reuse an old output directory for a new run;
- copy a model artifact and describe the copy as a fresh training run;
- silently change metrics, data splits, training objectives, or model-selection rules;
- use test data or answer labels to select a model artifact unless the claim explicitly permits it;
- expand the experiment scope beyond the approved plan;
- describe a single successful run as stable or general;
- hide failed runs, failed seeds, or negative controls.
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.
- 6d ago First seen · 418 lines · 2,866 tokens per session scan A da02cb92d64b
researcher-agentsmd AGENTS.md is an instructions file published in the GitHub repository OnTheThirdDay/researcher-agentsmd (2 stars, last pushed 1mo ago), licensed MIT. It adds 2,866 tokens to every session, about $0.0143 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 2026-08-31.
Other instructions, from other repositories
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.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
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).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
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.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.