Borrowing it
Nothing to install: this file belongs to tbhb/vale-ai-tells. 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/tbhb/vale-ai-tells/main/.claude/skills/review-commit-message/SKILL.mdgit clone --depth 1 https://github.com/tbhb/vale-ai-tellsWrote 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/tbhb/vale-ai-tells/review-commit-message)<a href="https://agentmods.dev/skills/tbhb/vale-ai-tells/review-commit-message"><img src="https://agentmods.dev/badge/skills/tbhb/vale-ai-tells/review-commit-message/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/tbhb/vale-ai-tells/review-commit-message"><img src="https://agentmods.dev/badge/skills/tbhb/vale-ai-tells/review-commit-message.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 | $0.00083 | $0.01286 |
| Opus 5 | $0.00042 | $0.00643 |
| Sonnet 5 | $0.00017 | $0.00257 |
| Haiku 4.5 | $0.00008 | $0.00129 |
Grade A, and why
review-commit-message 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 9d 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review a drafted commit message
Review a drafted commit message against its staged diff and return a verdict. You're the independent check. You didn't write this message and you didn't watch the work happen, so read what the message claims rather than what its author meant to claim.
The repository
$ARGUMENTS
Treat the first word as the repository under review. An empty value means the current working directory. Bind it once and use it throughout:
REPO="${ARGUMENTS:-$(pwd)}"
A second word of --amend says this commit replaces the one at HEAD instead of following it. That changes which diff you read, and nothing else about your job.
Gather the inputs
Run these before judging anything:
cat "$REPO/COMMIT_AGENTMSG"for the draftgit -C "$REPO" diff --cached --name-statusfor the staged pathsgit -C "$REPO" diff --cachedfor the staged diffgit -C "$REPO" log -5 --pretty=format:'%h %s'for project style
Where the caller passed --amend, swap the two staged-diff commands for these:
git -C "$REPO" diff --cached --name-status HEAD~1git -C "$REPO" diff --cached HEAD~1
Those show the amended commit's full contents, meaning the existing commit plus whatever the author has staged since. Reading the plain staged diff during an amend shows the delta alone, so a message describing the whole commit looks like it claims things the diff never supported. That mistake produces confident, wrong findings.
A missing or empty draft, or an empty staged diff, is itself a finding. Report it and stop.
What to check
Work these four groups. Every finding names the exact offending text and the fix.
Truthfulness
The message describes this diff and no other.
- Flag any claim the staged diff doesn't support. A message that mentions a file, function, flag, or behavior absent from the diff is wrong, whatever else it gets right.
- Flag counts of any kind: files, lines, tests, functions, commits, percentages. A count goes stale as soon as other work merges, and it pads a message rather than informing it.
- Flag results nobody verified: benchmark figures,
fixes the flake,no longer leaks, claims about what CI does.
What ships with it
1 file 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.
- 9d ago First seen · 110 lines · 83 tokens per session scan A 1e1d03a5fde6
review-commit-message is a skill published in the GitHub repository tbhb/vale-ai-tells (87 stars, last pushed today), licensed MIT. It adds 83 tokens to every session and 1,286 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
anti-slop
Remove AI slop from any voice-bearing prose — original posts, threads, articles, long-form, emails, docs, READMEs, marketing copy, bios, scripts. Use when drafting text meant to sound like a specific person or brand, when rewriting text that reads generic, corporate, or AI-generated, or when asked to humanize…
kill-slop
Audit a file or draft for AI slop and off-voice lines against the author's bound voice, report findings with in-voice swaps, then apply approved fixes. Use when the user says "kill slop", "/kill-slop [file]", "find the slop in this", "audit this for slop", or wants a deck, article, page, or draft cleaned to sound like…
requesting-code-review
Use when completing tasks, implementing major features, or before merging to verify work meets requirements.
github-pr-workflow
Prepare a GitHub pull request from a feature branch — branch hygiene, commit shape, title/body, verification notes, screenshots for UI work, and replies to review comments.
review-delta
Review only changes since last commit using impact analysis. Token-efficient delta review with automatic blast-radius detection.
work-unit-commits
Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.