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/juanmhidalgo/claude-plugins/fixnpx skills add juanmhidalgo/claude-plugins --skill fixgit clone --depth 1 https://github.com/juanmhidalgo/claude-pluginsWrote 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/juanmhidalgo/claude-plugins/fix)<a href="https://agentmods.dev/skills/juanmhidalgo/claude-plugins/fix"><img src="https://agentmods.dev/badge/skills/juanmhidalgo/claude-plugins/fix.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 | $0.00041 | $0.01086 |
| Opus 5 | $0.00020 | $0.00543 |
| Sonnet 5 | $0.00008 | $0.00217 |
| Haiku 4.5 | $0.00004 | $0.00109 |
Grade A, and why
fix 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 yesterday.
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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context
- Repository: !
git remote get-url origin 2>/dev/null || echo "no remote" - Current branch: !
git branch --show-current - Working tree clean: !
git status --porcelain | head -5 | wc -l | xargs -I{} sh -c 'if [ {} -eq 0 ]; then echo "yes"; else echo "no — {} uncommitted changes"; fi'
Issue to Fix
URL: $ARGUMENTS
Workflow
Follow these phases in order. Do NOT skip phases or advance without user approval.
Phase 1: Fetch Issue
- Validate the argument. It must be a GitHub Issue URL matching
https://github.com/{owner}/{repo}/issues/{number}. If invalid, STOP and ask for a valid URL. - Extract
owner,repo, andissue numberfrom the URL. - Fetch the issue:
If the issue is closed, warn the user and ask whether to proceed.gh issue view {number} --repo {owner}/{repo} --json title,body,labels,comments,assignees,milestone,state - Summarize to the user: title, labels, reproduction steps, expected vs actual behavior, error messages, and relevant comments. Flag any mentions of other repositories.
- Check for linked PRs or duplicates referenced in the body or comments.
Phase 2: Branch
- If there are uncommitted changes, warn and suggest stashing.
- Create a fix branch:
git checkout -b fix/issue-{number}-{slug}(slug: 3-4 lowercase hyphenated words from the title). - Confirm branch creation.
Phase 3: Explore
- Start from clues in the issue: error messages, file paths, function names, stack traces.
- Widen if needed: keyword search,
git log --oneline -20 -- {path}, related test files. - Build the picture: which files, what's wrong, what's correct, localized or cross-cutting.
If exploration exceeds 10 minutes without a clear picture, STOP and present findings. This limit is intentionally tighter than the global 15-minute limit — a single issue should converge faster or needs user guidance.
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.
- yesterday First seen · 115 lines · 41 tokens per session scan A e7f68b79f599
fix is a skill published in the GitHub repository juanmhidalgo/claude-plugins (8 stars, last pushed 10d ago), licensed MIT. It adds 41 tokens to every session and 1,086 once invoked, about $0.0002 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 2026-09-03.
Other skills, from other repositories
issue
Use when starting a chain from a GitHub issue — turning an issue URL or number into a triaged, planned, dispatched, and reviewed pull request. Classifies the thread (bug → root-cause discipline, feature → plan chain, question → drafted reply), synthesizes a spec from the issue's own acceptance criteria, then runs the…
github
Prepare GitHub issues, pull requests, reviews, and release notes for Zhin projects. Use when asked to write an issue, PR description, changelog entry, or review comment. Triggers: 写 issue, PR 描述, 提 PR, release notes, gh pr.
github-api
Call the GitHub REST API from Fermi (issues, PRs, file commits, binary commits via Git Data API) with correct auth and UTF-8 handling.
github-integration
GitHub 集成 Skill,支持创建/查询 Issue、PR,获取仓库信息。用于 Agent 与 GitHub 协作。.
pr
Use when reviewing an incoming GitHub pull request — runs the multi-level (L1-L5) audit against the PR's real diff range, posts findings as one batched review (inline, summary, or local-only), offers the standard fix chain on NEEDSFIX, and optionally merges. The maintainer-side counterpart to /hyperflow:issue. Trigger…
fix-issue
Fixes GitHub issues using parallel analysis agents for root cause investigation, code exploration, and regression detection. Reads issue context from gh CLI, searches codebase and memory for related patterns, generates a fix with tests, and links the resolution back to the issue via PR. Includes prevention analysis to…