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/fix-pr/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/fix-pr)<a href="https://agentmods.dev/skills/tbhb/vale-ai-tells/fix-pr"><img src="https://agentmods.dev/badge/skills/tbhb/vale-ai-tells/fix-pr/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/fix-pr"><img src="https://agentmods.dev/badge/skills/tbhb/vale-ai-tells/fix-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 108 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.00079 | $0.01736 |
| Opus 5 | $0.00039 | $0.00868 |
| Sonnet 5 | $0.00016 | $0.00347 |
| Haiku 4.5 | $0.00008 | $0.00174 |
Grade A, and why
fix-pr 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 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.
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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fix a failing pull request
Take a red pull request and make the checks pass. This skill ends after you commit a fix to the branch and push it. Confirming the result belongs to watch-pr, and merging belongs to merge-pr.
A guard hook runs alongside. It refuses a log sweep that goes around the diagnosis below, while leaving one job's full log open to read, because that's the real next step once the printed tail runs short.
Which pull request
$ARGUMENTS names the pull request number when the caller knows it. An empty value means whatever is open for the current branch.
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.
- Diagnose the failures
- Reproduce each one locally
- Fix the cause
- Commit through the commit skill
- Bring the description forward
- Push and hand back
Step 1: diagnose
bash .claude/skills/fix-pr/scripts/diagnose.sh <number>
One call gets the failing jobs, the tail of each failing step's log, and the local task the script maps each job to. Read that output before running anything else. Going straight to gh run view repeats work the script already did.
The script also compares the local checkout against the commit CI tested. Stop when it reports a mismatch. The logs then describe code this worktree no longer carries, so a fix aimed at them reaches the wrong revision. Check out the branch the pull request names, or pull it forward, and diagnose again.
Step 2: reproduce
Run the task the script named for each failure. Reproducing first is what separates a fix from a guess.
The mapping from job name to task is a guess, so treat a task that passes locally as a signal rather than a contradiction. Look for the explanation among these:
- The job runs something the task doesn't. Read the workflow.
- The failure depends on the environment, such as a pinned tool version or a container image the worktree isn't running.
- The failure is a flake, which makes the run worth repeating before anything changes.
- A stale branch. CI tested it merged with a base this worktree doesn't have, and the gate that fails arrived on that base. Nothing here reproduces it until the branch moves, so run the
rebaseskill and diagnose again.
What ships with it
4 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 · 130 lines · 79 tokens per session scan A 95515d765339
fix-pr is a skill published in the GitHub repository tbhb/vale-ai-tells (92 stars, last pushed today), licensed MIT. It adds 79 tokens to every session and 1,736 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.
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