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/tbhb/vale-ai-tells/commitnpx skills add tbhb/vale-ai-tells --skill commitgit 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/commit)<a href="https://agentmods.dev/skills/tbhb/vale-ai-tells/commit"><img src="https://agentmods.dev/badge/skills/tbhb/vale-ai-tells/commit.svg" alt="Measured on agentmods" 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 | $0.00086 | $0.03020 |
| Opus 5 | $0.00043 | $0.01510 |
| Sonnet 5 | $0.00017 | $0.00604 |
| Haiku 4.5 | $0.00009 | $0.00302 |
Grade A, and why
commit 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.
How it starts
The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Commit workflow
Work the steps in order. A guard hook runs alongside them and refuses whole-tree staging along with any git commit you write out yourself. Step 8 names the one script that commits, and that script refuses an inline -m message, a --no-verify, and a draft the reviewer hasn't seen in its current form.
Those hooks stay registered for the rest of the session so they carry a scope. Preflight records the commit HEAD sits on now, and the guard refuses while HEAD is still there. Step 8 moves HEAD past that mark, and the guard refuses nothing after that. Work later in the session is none of the guard's business. A second commit means invoking this skill again rather than carrying on from here.
Preflight
!bash ${CLAUDE_SKILL_DIR}/scripts/preflight.sh
Step 0: the checklist
Track these steps with the session's task-list tools where it carries them. Newer harnesses leave those tools out by default, and a session without them works the list in order as written. They're the checklist the rest of this document expands.
- Choose the rebase base
- Group the changes into atomic commits
- Stage the paths for this commit
- Draft the message in COMMIT_AGENTMSG
- Pass the prose gates with fix-prose
- Review the draft with review-commit-message
- Run the commit-msg gates
- Confirm the message with the operator
- Commit and rebase
Stop before any of it if preflight reports a rebase, merge, or cherry-pick in progress, or a missing precondition. Say what's wrong and hand back.
Step 1: choose the rebase base
Preflight computed this under == rebase base ==. Take its recommendation:
- Local default branch carries everything the remote has, so rebase onto the local branch.
- Local default branch sits behind the remote, so rebase onto
origin/<default>and skip the stale local copy.
Record the base now. Step 9 rebases onto it without asking again. Worktrees under .claude/worktrees are the usual layout here, and each one has its own checkout of the branch.
What ships with it
5 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.
- 5d ago First seen · 230 lines · 86 tokens per session scan A 66c681663e47
commit is a skill published in the GitHub repository tbhb/vale-ai-tells (83 stars, last pushed today), licensed MIT. It adds 86 tokens to every session and 3,020 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…
humanizer
Humanize and de-slop AI-sounding prose while preserving meaning, specific detail, and genuine human quirks. When a voice sample or style profile is available, rewrite in that writer's actual voice. Remove recurring AI tells such as inflated significance, stock vocabulary, uniform rhythm, excessive hedging, formulaic…
authenticity-check
Score how authentically text reads as a real human author's work, flag spans that read as AI-generated, AI-templated, or generically derivative, and run a separate read-only scan for suspicious Unicode provenance carriers. Return an authenticity band, a 0-100 score, provenance signals, and span-level reasons. Use when…
ai-slop-detector
Universal prose audit. Scores writing on TWO axes — AI-Slop (does this read like AI wrote it?) and Comprehension (can a fresh reader follow this?). Use PROACTIVELY as a mandatory final QA pass on ANY prose generated for humans to read — every email (internal or external), proposal, report, status update, blog post…
humanizer-czech
Odstraň znaky AI-generovaného psaní z českého textu. Použij při editaci nebo revizi textu, aby zněl přirozeněji a lidštěji. Detekuje a opravuje 27 vzorců včetně: nafouklého významu, propagačního jazyka, anglického slovosledu, kalků, nominalizace, monotónního rytmu, nadužívání spojek, typických českých AI klišé…