contentrain-serve

contentrain-serve is a skill for Claude Code, Codex from Contentrain/ai. It costs 32 tokens per session (1,009 once invoked), scanned A, original, MIT.

A local review page for inspecting Contentrain content and proposed changes in a browser. It also supports plans for making content more consistent.

In plain words
What is it for?
Use it to start the Contentrain review interface, inspect content or branches, and hand proposed changes to a developer for approval.
Why use it?
It gives developers a visual way to check extracted content, models, history, and pending changes before approving them.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/contentrain/ai/contentrain-serve
Any agent
npx skills add Contentrain/ai --skill contentrain-serve
Clone the repo
git clone --depth 1 https://github.com/Contentrain/ai

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for contentrain-serve

README.md
[![agentmods](https://agentmods.dev/badge/skills/contentrain/ai/contentrain-serve.svg)](https://agentmods.dev/skills/contentrain/ai/contentrain-serve)
Your own site
<a href="https://agentmods.dev/skills/contentrain/ai/contentrain-serve"><img src="https://agentmods.dev/badge/skills/contentrain/ai/contentrain-serve.svg" alt="Measured on agentmods" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,009 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00032 $0.01009
Opus 5 $0.00016 $0.00504
Sonnet 5 $0.00006 $0.00202
Haiku 4.5 $0.00003 $0.00101

Measured 4d ago against content hash ed64dc83baee, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

contentrain-serve 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.

packages/skills/skills/contentrain-serve/SKILL.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Review the Project with contentrain serve

Start the local review UI as a bridge between agent and developer.


When to Use

Use this when:

  • a normalize plan, branch, or validation result needs developer review
  • the developer wants to browse models, content, or history visually
  • another skill needs to hand off to the UI for approval (normalize, review)

Steps

1. Check if Serve is Already Running

Before starting a new instance, check if port 3333 is already in use:

lsof -ti:3333

If a process is running, serve is already up — skip to Step 3.

2. Start Serve

Run from the project root (where .contentrain/ lives):

contentrain serve

Optional flags:

  • --port (default: 3333)
  • --host (default: localhost)
  • --open=false (prevent auto-opening browser)
  • --stdio (MCP stdio transport for IDE integration — no web UI)

Wait for the "Contentrain Serve" banner confirming the server is ready.

3. Direct the Developer to the Right Page

Based on the current context, tell the developer exactly where to go:

Context URL What to do
Normalize plan ready http://localhost:3333/normalize Review extractions, approve or reject
Pending branches http://localhost:3333/branches Review and merge branches
Validation issues http://localhost:3333/validate Inspect errors and warnings
Content browsing http://localhost:3333/content Browse entries and models
General overview http://localhost:3333 Dashboard with project stats

4. Wait for Developer Action

After directing the developer to the UI:

  • Normalize flow: Check .contentrain/normalize-plan.json — if deleted, check for new branches to determine approve vs reject
  • Branch flow: Check branch list — if branch was merged or deleted, proceed accordingly
  • Validation flow: Re-read validation results after developer reviews

The UI communicates back through filesystem changes (plan files, branches, context.json). Poll these to detect the developer's decision.

Read the full file on GitHub · 122 lines

Changes

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.

  1. 4d ago First seen · 122 lines · 32 tokens per session scan A ed64dc83baee

Subscribe to this mod's changes

contentrain-serve is a skill published in the GitHub repository Contentrain/ai (4 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 1,009 once invoked, about $0.0002 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.

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