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 skills add Contentrain/ai --skill contentrain-initgit clone --depth 1 https://github.com/Contentrain/aiWrote 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/skills/contentrain/ai/contentrain-init)<a href="https://agentmods.dev/skills/contentrain/ai/contentrain-init"><img src="https://agentmods.dev/badge/skills/contentrain/ai/contentrain-init/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/skills/contentrain/ai/contentrain-init"><img src="https://agentmods.dev/badge/skills/contentrain/ai/contentrain-init.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 | $0.00032 | $0.00964 |
| Opus 5.5 | $0.00013 | $0.00386 |
| Sonnet 5.5 | $0.00006 | $0.00193 |
| Haiku 4.5 | $0.00003 | $0.00096 |
Grade A, and why
contentrain-init 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Initialize Contentrain in a Project
Set up Contentrain content infrastructure in an existing project.
When to Use
The user wants to add Contentrain to their project, or says something like "set up contentrain", "initialize contentrain", "add content management".
Steps
1. Detect the Tech Stack
Read package.json to identify the framework:
| Dependency | Stack |
|---|---|
nuxt |
Nuxt 3 |
next |
Next.js |
@astrojs/astro or astro |
Astro |
@sveltejs/kit |
SvelteKit |
If none match, treat as a generic Node.js project. Report the detected stack to the user before proceeding.
2. Ask for Configuration
Ask the user for:
- Supported locales: Which languages will the project support? Default:
["en"]. Use ISO 639-1 codes. - Source locale: Which locale is the primary/source locale? Default:
"en". - Domain names: Suggest domains based on the project structure (e.g.,
marketing,blog,app,docs). Ask the user to confirm or modify.
3. Initialize the Project
Call the MCP tool:
contentrain_init(stack: "<detected>", locales: ["en", ...], domains: ["marketing", ...])
This creates the .contentrain/ directory structure, config.json, and initial context.json.
4. Analyze Project Conventions
After initialization, review the project for conventions to inform content creation:
- Tone: Analyze existing copy in the project (README, landing page, UI text) to determine the appropriate tone (e.g.,
professional,casual,technical). - Naming conventions: Note any patterns in file naming, component naming, or content structure.
Note: Do NOT manually edit
context.json. It is managed automatically by MCP tools and updated after every write operation.
5. Suggest Initial Models
Based on the project analysis, suggest models that would be useful:
- If the project has a landing page: suggest
hero(singleton),features(singleton or collection). - If the project has a blog section: suggest
blog-post(document),categories(collection),authors(collection). - If the project has UI text: suggest
ui-labels(dictionary),error-messages(dictionary).
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 · 117 lines · 32 tokens per session scan A e1f577c8cd62
contentrain-init is a skill published in the GitHub repository Contentrain/ai (6 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 964 once invoked, about $0.0001 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 2026-08-31.
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