contentrain-normalize

A two-stage skill for moving hardcoded website text into Contentrain, a content-management system. It first extracts text into .contentrain files, then can replace source-code text with references to that content.

In plain words
What is it for?
Useful for scanning a project, extracting its content, reviewing proposed changes, and connecting selected source files to managed content.
Why use it?
It makes text easier to manage, translate, and publish without editing application code each time.

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

Made for: Claude Code, Codex.

Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,062 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 $0.00053 $0.03062
Opus 5 $0.00026 $0.01531
Sonnet 5 $0.00011 $0.00612
Haiku 4.5 $0.00005 $0.00306

Measured 2d ago against content hash 224aebd0e50f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

contentrain-normalize 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.

packages/skills/skills/contentrain-normalize/SKILL.md · 294 lines

How it starts

The opening of the file, as written. The whole thing — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Contentrain Normalize

Normalize converts a codebase with hardcoded strings into a Contentrain-managed content architecture. It runs in two independent phases, each producing a separate branch for review.

  • Phase 1 (Extraction): Pull content from source code into .contentrain/ structure. Source files are NOT modified.
  • Phase 2 (Reuse): Patch source files to replace hardcoded strings with content references. Requires completed extraction.

Phase 1 alone is valuable: content becomes manageable in Studio, translatable, and publishable without touching source code.


MUST Rules

  • MUST scan before extract (contentrain_scancontentrain_apply)
  • MUST dry_run: true before dry_run: false for every contentrain_apply call
  • MUST merge Phase 1 branch before starting Phase 2
  • MUST run npx contentrain generate after Phase 2 completes
  • MUST NOT reuse without scoped model or domain (whole-project patching is blocked)
  • MUST NOT patch .contentrain/ files via reuse (content files are read-only for reuse)
  • MUST NOT exceed 100 patches per contentrain_apply call

Transport Requirements

Normalize (contentrain_scan and contentrain_apply) requires local disk access — AST scanners walk the source tree and patch files in place. It runs only on a LocalProvider (stdio transport, or an HTTP transport configured with a LocalProvider).

Remote providers (GitHubProvider, GitLabProvider, future BitbucketProvider) expose astScan: false, sourceRead: false, and sourceWrite: false. Calling these tools over a remote provider returns a uniform capability error:

{
  "error": "contentrain_scan requires local filesystem access.",
  "capability_required": "astScan",
  "hint": "This tool is unavailable when MCP is driven by a remote provider. Use a LocalProvider or the stdio transport."
}

If the agent is driving a remote-only MCP session, normalize must run in a separate local-checkout session before the extracted content branch is pushed.

Read the full file on GitHub · 294 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2d ago First seen · 294 lines · 53 tokens per session scan A 224aebd0e50f

Subscribe to this mod's changes

contentrain-normalize is a skill published in the GitHub repository Contentrain/ai (4 stars, last pushed 2d ago), licensed MIT. It adds 53 tokens to every session and 3,062 once invoked, about $0.0003 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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