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 skills/contentrain/ai/contentrain-reviewnpx skills add Contentrain/ai --skill contentrain-reviewgit 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-review)<a href="https://agentmods.dev/skills/contentrain/ai/contentrain-review"><img src="https://agentmods.dev/badge/skills/contentrain/ai/contentrain-review.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 | $0.00029 | $0.01655 |
| Opus 5 | $0.00015 | $0.00827 |
| Sonnet 5 | $0.00006 | $0.00331 |
| Haiku 4.5 | $0.00003 | $0.00166 |
Grade A, and why
contentrain-review 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 5d 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 — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Review Pending Content Changes
Review content changes on Contentrain branches, apply quality checks, and recommend approval or rejection.
When to Use
The user wants to review content quality, audit existing entries, check pending changes, or run a pre-publish checklist. Triggers: "review content", "check pending changes", "review the contentrain branch", "content QA", "audit content", "pre-publish check".
Steps
1. Check Project State
Call contentrain_status to understand the current project:
- All models, their kinds, domains, and entry counts.
- Configured locales and source locale.
- Pending branches or unsubmitted changes.
- Workflow mode (auto-merge or review).
2. List Content for Review
For each model (or the user-specified scope), call contentrain_content_list(model: "<modelId>", locale: "<locale>"):
- Retrieve entries for the source locale first.
- For i18n models, also retrieve entries for each target locale.
- Note entry counts per locale to identify i18n coverage gaps.
If reviewing a specific branch, list the contentrain/* branches and show:
- Branch name (indicates operation type: extract, reuse, content-save, model-save).
- Number of changed files.
- Last commit date.
3. Run Automated Validation
Call contentrain_validate to get the automated validation report:
- Schema compliance errors (missing required fields, type mismatches).
- Referential integrity issues (broken relation references).
- i18n completeness gaps (missing locale entries).
- Content policy violations.
4. Apply Quality Checklist
Go through each category and report findings:
4.1 Content Quality (from content-quality.md)
- All required fields are populated with real, non-placeholder values.
- Text fields respect
min/maxconstraints. - No placeholder text (lorem ipsum, TODO, TBD, [insert here]).
- Tone is consistent with
context.json→conventions.tone. - Vocabulary terms from
vocabulary.jsonare used consistently. - Collection entries have no duplicate
uniquefield values. - Content follows the correct content type pattern (blog post, landing page, docs, etc.).
- No duplicate content across entries.
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.
- 5d ago First seen · 194 lines · 29 tokens per session scan A 4ce65a771f88
contentrain-review is a skill published in the GitHub repository Contentrain/ai (4 stars, last pushed yesterday), licensed MIT. It adds 29 tokens to every session and 1,655 once invoked, about $0.0001 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 skills, from other repositories
data-charts-tako
Search and visualize the world's data - get charts, insights, and embeddable knowledge cards for finance, economics, demographics, sports, and more.
apollo-lead-finder
Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact). Creates Apollo lists. Deduplicates against existing contacts by LinkedIn URL.
monorepo-management
Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.
browse-and-evaluate
Use when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing. Always use --fields to limit output size and --dry-run before committing to an install.
render-3d-product-showcase
Assemble a premium 3D product-showcase ad from a config — four beat clips (an orbiting hero rotation, a macro push-in, a physics reveal, a typographic close) normalized to the brand-color canvas, hard-concatenated in order, closed on a deterministic Playwright brand end card, and mixed under one instrumental bed at…
render-airdrop-carousel
Assemble a viral iOS "AirDrop" notification-carousel video ad (≈6–8s, 9:16) from a brand line plus 6–16 real product photos — a native AirDrop share-sheet card ("Brand would like to share a · Decline / Accept") springs up and its preview window CYCLES through the products, landing on a range/lineup payoff with an…