Borrowing it
Nothing to install: this file belongs to shir-danishyar/humanize. 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/shir-danishyar/humanize/main/AGENTS.mdgit clone --depth 1 https://github.com/shir-danishyar/humanizeWrote 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/shir-danishyar/humanize/agents-md)<a href="https://agentmods.dev/instructions/shir-danishyar/humanize/agents-md"><img src="https://agentmods.dev/badge/instructions/shir-danishyar/humanize/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 | $0.00277 | $0.00277 |
| Opus 5 | $0.00138 | $0.00138 |
| Sonnet 5 | $0.00055 | $0.00055 |
| Haiku 4.5 | $0.00028 | $0.00028 |
Grade A, and why
humanize 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 3d 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.
What it actually says
Instructions for agent harnesses
This repository is an Agent Skills-format skill. To use it:
- Load
SKILL.mdat the repo root. Its frontmatterdescriptiontells you when the skill applies: any audience-facing prose task (emails, posts, articles, marketing copy, reports), or an explicit request to humanize or de-AI text. - Follow SKILL.md's workflow. It will direct you to read the files under
references/on demand —patterns.mdfor the full pattern catalog,vocabulary.mdfor word substitutions,voice.mdwhen the user provides writing samples or avoice-profile.mdexists. Don't preload them; they're structured for progressive disclosure. - Optionally verify output mechanically:
python3 scripts/ai_pattern_lint.py <file>reports AI-pattern density (exit 0 = clean). Python 3.9+, no dependencies.
Two rules bind harder than the rest: never invent a fact, number, name, or quote that the source or the user did not supply; and when rewriting a file, change only the prose (leave code, front matter, data, and link targets alone).
Do not apply this skill to code, commit messages, configuration, or legal text. User instructions always override the skill's defaults.
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.
- 3d ago Changed · +2 lines · +53 tokens per session 47324b8268a1
- 6d ago First seen · 10 lines · 224 tokens per session scan A a71fd81713bf
humanize AGENTS.md is an instructions file published in the GitHub repository shir-danishyar/humanize (15 stars, last pushed 3d ago), licensed MIT. It adds 277 tokens to every session, about $0.0014 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
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AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
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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.