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-validate-fixgit 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-validate-fix)<a href="https://agentmods.dev/skills/contentrain/ai/contentrain-validate-fix"><img src="https://agentmods.dev/badge/skills/contentrain/ai/contentrain-validate-fix/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-validate-fix"><img src="https://agentmods.dev/badge/skills/contentrain/ai/contentrain-validate-fix.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 | $0.00656 |
| Opus 5.5 | $0.00013 | $0.00262 |
| Sonnet 5.5 | $0.00006 | $0.00131 |
| Haiku 4.5 | $0.00003 | $0.00066 |
Grade A, and why
contentrain-validate-fix 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Validate and Fix Content Issues
Diagnose validation failures, apply safe fixes, and re-check the project.
When to Use
Use this when:
- validation reports errors or warnings
- the user asks to fix schema/content issues
- a write operation succeeded but the project still needs verification
Steps
1. Run Validation
Call contentrain_validate first.
Group results into:
- schema/type errors
- missing required fields
- relation integrity problems
- locale completeness issues
- canonical format warnings
2. Decide Auto-fix vs Manual Fix
Auto-fix candidates:
- canonical formatting
- orphan metadata cleanup
- stray non-i18n meta layout (an
i18n: falsemodel with per-locale meta files left by older versions) — pruned or migrated deterministically, never merging or downgrading a status publish_at/expire_atcopies an oldercontent_saveleft in document frontmatter — stripped only when the meta record holds the same key, so the value is never lost and an author's own frontmatter field is never touched- a missing model
title_field— backfilled by the same ranking Studio's title resolver uses (required name-like field first; slug/url/code never inferred), reported as a notice naming the rule. Read it: if the pick is wrong, correct it withcontentrain_model_save - structural housekeeping reported by the validator
Manual fix candidates:
- missing required content
- wrong field values
- broken relations
- incorrect slugs/IDs
- a non-i18n "Meta layout mismatch" with several strays and no default-locale
meta (ambiguous —
fix: trueleaves it; pick the authoritative file yourself)
3. Use Auto-fix Carefully
If the issues are structural, run:
{
"fix": true
}
After that, validate again.
4. Fix Semantic Errors
For real content or schema issues:
- inspect the model with
contentrain_describe - patch content with
contentrain_content_save - patch schema with
contentrain_model_save
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 Changed · +7 lines 2abb246d2947
- 1mo ago First seen · 104 lines · 32 tokens per session scan A 3f2f728942d8
contentrain-validate-fix 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 656 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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