Borrowing it
Nothing to install: this file belongs to gwenneg/ai-mentor. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/gwenneg/ai-mentor/main/.claude/skills/ai-mentor-update/SKILL.mdgit clone --depth 1 https://github.com/gwenneg/ai-mentorWrote 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/gwenneg/ai-mentor/ai-mentor-update)<a href="https://agentmods.dev/skills/gwenneg/ai-mentor/ai-mentor-update"><img src="https://agentmods.dev/badge/skills/gwenneg/ai-mentor/ai-mentor-update/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/gwenneg/ai-mentor/ai-mentor-update"><img src="https://agentmods.dev/badge/skills/gwenneg/ai-mentor/ai-mentor-update.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 | $0.00057 | $0.04615 |
| Opus 5 | $0.00028 | $0.02308 |
| Sonnet 5 | $0.00011 | $0.00923 |
| Haiku 4.5 | $0.00006 | $0.00462 |
Grade C, and why
ai-mentor-update scanned grade C with 2 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 11d 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -s https://raw.githubusercontent.com/anthropics/claude-plugins-official/main/.claude-plugin/marketplace.json | python3 -c "import json,sys; [print(p['name']) for p in json.load(sys.stdin)['plugins']]" Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s https://code.claude.com/docs/en/whats-new/index.md How it starts
The opening of the file, as written. The whole thing — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Mentor Update
You are a content maintenance tool for the ai-mentor plugin. Your job is to keep the goal and approach files structurally consistent, factually accurate, and up to date.
All paths below are relative to the repo root.
Modes
Interactive (default): follow the steps as written, asking the user at each decision point.
Non-interactive (--auto): when $ARGUMENTS contains --auto, never ask a question and never wait for input — there is no user present (this mode runs headless in CI). Parse from the arguments:
--auto <steps>— comma-separated step numbers to run, using the Step headings below (2 = structural audit, 3 = content verification, 4 = process new changelogs, 5 = plugin catalog sync), e.g.--auto 4,5--files N— Step 3 scope: process the N oldest-verified files (default: 5)
The routine weekly run is --auto 4,5: process new changelogs and sync the plugin catalog. Steps 2 and 3 are deeper audits for occasional use — Step 2 largely duplicates the CI gate, and Step 3 re-verifies old content that changelog processing doesn't touch.
Auto-mode overrides, in addition to skipping every question below:
- Step 2: apply only unambiguous structural fixes (broken separator, wrong field order); report anything requiring judgment instead of fixing it. Note: CI also runs the catalog lint (
go -C tools/catalog-lint run .) as a deterministic gate — prefer reporting over creative fixing. - Step 3: process the N oldest-verified files with no per-file pause. Apply only changes that meet the "Recommended changes" bar (official-tier source + direct quote); list everything else under "needs manual verification" in the report without applying it.
- Step 4: process every digest not yet in the ledger; same evidence bar as Step 3; always append the ledger row for each processed digest.
- Step 5: apply additions and removals directly — the GitHub API response is authoritative.
- Never run
git commit,git push, or create branches — the calling workflow owns git. - Final output: end with a single markdown report (the caller uses it as a PR body) with two sections: Changes applied (file, change, source URL, supporting quote) and Not applied (finding + why it needs a human). If nothing changed, say so explicitly.
What ships with it
2 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.
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.
- 11d ago First seen · 311 lines · 57 tokens per session scan C 91d810778d0e
ai-mentor-update is a skill published in the GitHub repository gwenneg/ai-mentor (4 stars, last pushed 4d ago), licensed Apache-2.0. It adds 57 tokens to every session and 4,615 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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