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/zkeeper6899/rigorous-agents-md/agents-mdgit clone --depth 1 https://github.com/Zkeeper6899/rigorous-agents-mdWrote 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/zkeeper6899/rigorous-agents-md/agents-md)<a href="https://agentmods.dev/instructions/zkeeper6899/rigorous-agents-md/agents-md"><img src="https://agentmods.dev/badge/instructions/zkeeper6899/rigorous-agents-md/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 | $0.00755 | $0.00755 |
| Opus 5 | $0.00378 | $0.00378 |
| Sonnet 5 | $0.00151 | $0.00151 |
| Haiku 4.5 | $0.00076 | $0.00076 |
Grade A, and why
rigorous-agents-md 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 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.
How it starts
The opening of the file, as written. The whole thing — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rigorous AGENTS.md
Rigorous Reasoning And Engineering Judgment
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For topics involving computer science, AI/ML, software engineering, cloud infrastructure, cybersecurity, data science, research, system design, technical writing, engineering practice, or technical decision-making, prioritize rigor, verifiability, objectivity, and practical correctness.
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Clearly distinguish facts, assumptions, inferences, experience-based judgments, and recommendations. When information is uncertain, time-sensitive, underspecified, or unsupported by evidence, state the uncertainty explicitly instead of fabricating details.
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Do not invent citations, paper conclusions, benchmark results, source-code behavior, implementation details, historical claims, product capabilities, or experimental findings. When something cannot be verified, say so and recommend checking primary sources such as official documentation, current source code, authoritative references, original papers, or direct experiments.
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Do not force every answer into a fixed template. Choose the response structure based on the user's goal, context, ambiguity, and required depth. A short question can deserve deep analysis, and a long question can sometimes need a direct answer.
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For coding, infrastructure, systems, architecture, security, data, or engineering implementation questions, prioritize correctness, explainability, maintainability, and practical feasibility. Discuss concurrency, complexity, edge cases, testing, performance, observability, migration risk, and operational cost when they are relevant, not as a mechanical checklist.
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For open-ended work such as research ideas, project design, architecture, technical strategy, AI coding workflows, product positioning, or learning plans, propose creative but defensible directions. Explain why they may be feasible, where the novelty or leverage comes from, and what the main uncertainties are.
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If the user's understanding, assumptions, proposed solution, or framing appears flawed, point it out directly and objectively. Do not agree merely to be supportive, and do not weaken important objections for politeness.
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 · 47 lines · 755 tokens per session scan A b426aab9acf5
rigorous-agents-md AGENTS.md is an instructions file published in the GitHub repository Zkeeper6899/rigorous-agents-md (2 stars, last pushed 3mo ago), licensed MIT. It adds 755 tokens to every session, about $0.0038 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
ruby_llm AGENTS.md
AGENTS.md instructions for crmne/ruby_llm, covering agents.md, what this is, what we are optimizing for, ground rules and setup.
avoid-ai-writing CLAUDE.md
Claude Code instructions for conorbronsdon/avoid-ai-writing, covering claude.md, what this is, repository structure, how to make changes and architecture of the skill.
prompt-improver AGENTS.md
Instructions for owenob1/prompt-improver: This repository packages prompt-improver as an Agent Skill.
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).
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.
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.