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 jmagly/aiwg --skill editorial-correction-reviewgit clone --depth 1 https://github.com/jmagly/aiwgWrote 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/jmagly/aiwg/editorial-correction-review)<a href="https://agentmods.dev/skills/jmagly/aiwg/editorial-correction-review"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/editorial-correction-review/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/jmagly/aiwg/editorial-correction-review"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/editorial-correction-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00026 | $0.00263 |
| Opus 5 | $0.00013 | $0.00131 |
| Sonnet 5 | $0.00005 | $0.00053 |
| Haiku 4.5 | $0.00003 | $0.00026 |
Grade A, and why
editorial-correction-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.
What it actually says
Editorial Correction Review
Process
- Freeze silent edits and preserve the challenged version/hash.
- Collect the complaint, original sources, contrary evidence, response, safety concerns, retention holds, and all downstream locations.
- Create a linked new version and correction note. Use
withheldduring review andcanceledonly for permanent withdrawal from public reuse. - Update owned caches, feeds, APIs, indexes, and exports; record third-party reindex/removal as requested or observed, never guaranteed global deletion.
- Re-run source, citation, privacy, freshness, accessibility, and publish gates; a named human approves release.
Output
A correction-record artifact and completion evidence per downstream target.
References
schemas/correction-record.schema.jsonrules/publication-human-review.mddocs/research/control-source-matrix.md
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 · 35 lines · 26 tokens per session scan A bc512035218a
editorial-correction-review is a skill published in the GitHub repository jmagly/aiwg (210 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 263 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 2026-09-05.
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