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/contentrain/ai/agents-mdgit clone --depth 1 https://github.com/Contentrain/aiWhat 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 | $0.01091 | $0.01091 |
| Opus 5 | $0.00545 | $0.00545 |
| Sonnet 5 | $0.00218 | $0.00218 |
| Haiku 4.5 | $0.00109 | $0.00109 |
Grade A, and why
ai 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 2d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Contentrain AI
Git-based, AI-first content governance infrastructure. Agent extracts or updates content → Contentrain standardizes → Human reviews → Any platform consumes.
What this repo is
MIT-licensed monorepo for Contentrain's open-source packages: MCP tools, CLI, TypeScript types, AI rules, universal query SDK, and agent skills.
Agent Skills
This repo ships 15 Agent Skills following the Agent Skills standard. Install them with:
npx skills add contentrain/contentrain-ai --skill='*'
Or install a specific skill:
npx skills add contentrain/contentrain-ai --skill='contentrain-normalize'
Skills are located at packages/skills/skills/*/SKILL.md:
| Skill | When to use |
|---|---|
contentrain |
Working with .contentrain/ directory, MCP tools, content formats |
contentrain-normalize |
Extracting hardcoded strings, patching source files with content refs |
contentrain-quality |
Content quality checks, SEO, accessibility, media rules |
contentrain-sdk |
Using @contentrain/query, #contentrain imports, QueryBuilder |
contentrain-content |
Creating/updating content entries for existing models |
contentrain-model |
Designing and saving model definitions |
contentrain-init |
Initializing a new Contentrain project |
contentrain-bulk |
Batch operations on content entries |
contentrain-validate-fix |
Validating content and auto-fixing structural issues |
contentrain-review |
Reviewing content changes before publishing |
contentrain-translate |
Translating content across supported locales |
contentrain-generate |
Generating the typed SDK client from models |
contentrain-serve |
Starting the local review UI |
contentrain-diff |
Viewing content diffs between branches |
contentrain-doctor |
Diagnosing project health issues |
Essential rules (always-loaded)
Load packages/rules/essential/contentrain-essentials.md (~120 lines) for compact guardrails covering:
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.
- 2d ago First seen · 103 lines · 1,091 tokens per session scan A 1b52edcfdf54
ai AGENTS.md is an instructions file published in the GitHub repository Contentrain/ai (4 stars, last pushed 2d ago), licensed MIT. It adds 1,091 tokens to every session, about $0.0055 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
skills-hub AGENTS.md
Instructions for qufei1993/skills-hub, covering skills hub - project rules, tech stack, common commands, directory structure and architecture.
spec-kit-zh AGENTS.md
Instructions for loulanyue/spec-kit-zh, covering agents.md, about spec kit and specify, general practices, adding new agent support and current supported agents.
EGC copilot-instructions.md
Instructions for Fmarzochi/EGC, covering copilot instructions for egc, repository conventions, readme and translations, code review priorities and egc project memory.
scriveno AGENTS.md
Instructions for hannsxpeter/scriveno, covering project, constraints, technology stack, architecture constraint and recommended stack.
vibe-roast dashboard.instructions.md
Instructions for PinkR1ver/vibe-roast, a project described as: Local-first AI coding personality profiler, usage dashboard, and evidence-grounded roast.
globalize-skills CLAUDE.md
Instructions for globalize-now/globalize-skills, covering globalization skills, repository structure, conventions, installing a skill and install a single skill into the current project.