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-validate-fixnpx skills add Contentrain/ai --skill contentrain-validate-fixgit clone --depth 1 https://github.com/Contentrain/aiWhat 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 | $0.00032 | $0.00537 |
| Opus 5 | $0.00016 | $0.00269 |
| Sonnet 5 | $0.00006 | $0.00107 |
| Haiku 4.5 | $0.00003 | $0.00054 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 104 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 - 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
Do not claim the project is valid until validation is rerun.
5. Re-run Validation
Call contentrain_validate again and compare:
- errors reduced to zero
- remaining warnings acknowledged
6. Submit or Recommend Review
If validation is clean:
- call
contentrain_submitwhen pending review branches exist
If validation still fails:
- summarize remaining blockers precisely
- tell the user which model/entry needs manual attention
Related Skills
- contentrain-review — Full content review workflow
- contentrain-content — Fix content entries after validation errors
- contentrain — Core architecture and MCP tool catalog
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.
- 2d 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 (4 stars, last pushed 3d ago), licensed MIT. It adds 32 tokens to every session and 537 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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