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 skills add magic3007/dotfiles --skill analyze-prgit clone --depth 1 https://github.com/magic3007/dotfilesWrote 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/magic3007/dotfiles/analyze-pr)<a href="https://agentmods.dev/skills/magic3007/dotfiles/analyze-pr"><img src="https://agentmods.dev/badge/skills/magic3007/dotfiles/analyze-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/magic3007/dotfiles/analyze-pr"><img src="https://agentmods.dev/badge/skills/magic3007/dotfiles/analyze-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Data Exfiltration · line 36 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00060 | $0.01134 |
| Opus 5.5 | $0.00024 | $0.00454 |
| Sonnet 5.5 | $0.00012 | $0.00227 |
| Haiku 4.5 | $0.00006 | $0.00113 |
Grade A, and why
analyze-pr scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze Pull Request
Given a PR URL, fetch the code changes and web description, then generate a comprehensive analysis document. The PR is guaranteed to belong to the current local repository.
Workflow
Step 1: Parse the PR URL
Extract from the URL:
- Platform: GitHub or GitLab
- Owner/Org, Repo, PR Number
Supported formats:
https://github.com/{owner}/{repo}/pull/{number}
https://gitlab.com/{owner}/{repo}/-/merge_requests/{number}
Step 2: Fetch PR Metadata
Use the WebFetch tool to read the PR page and extract:
- PR title, description, author, labels, linked issues
- Review comments and discussion highlights
For GitHub PRs, also fetch the API endpoint for structured data:
https://api.github.com/repos/{owner}/{repo}/pulls/{number}
This gives you base.ref (base branch name), head.ref, additions, deletions, changed_files, etc.
Step 3: Fetch the PR Branch Locally
# Record current branch for later restore
ORIGINAL_BRANCH=$(git rev-parse --abbrev-ref HEAD)
# GitHub
git fetch origin pull/{number}/head:pr-{number}
# GitLab
git fetch origin merge-requests/{number}/head:mr-{number}
Do NOT checkout the PR branch — use it as a ref for diff only, to avoid disrupting the working tree.
Step 4: Generate the Diff
Use base.ref from Step 2 as the base branch (do NOT hardcode main):
BASE_BRANCH={base.ref from step 2}
# Changed file list
git diff --name-only origin/$BASE_BRANCH...pr-{number}
# Stats summary
git diff --stat origin/$BASE_BRANCH...pr-{number}
# Full diff
git diff origin/$BASE_BRANCH...pr-{number}
# Commit history
git log --oneline origin/$BASE_BRANCH..pr-{number}
Step 5: Analyze the Changes
For each changed file, understand:
- What changed: additions, deletions, modifications
- Why it changed: infer from commit messages, PR description, and code context
- Impact: which components/modules are affected
Group changes by category:
- New Features: new files, new functions, new APIs
- Bug Fixes: error handling, logic corrections
- Refactoring: code reorganization, naming changes
- Configuration: build, CI/CD, dependency changes
- Documentation: README, comments, docs
- Tests: new or modified tests
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.
- 1mo ago First seen · 180 lines · 60 tokens per session scan A 31d292d37b21
analyze-pr is a skill published in the GitHub repository magic3007/dotfiles (11 stars, last pushed 2d ago), licensed MIT. It adds 60 tokens to every session and 1,134 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
Other skills, from other repositories
merge-ready
Drive an existing pull request to a mergeable state: get CI green, resolve merge conflicts with the base branch, address and resolve review comments, trigger required bot reviews/approvals (e.g. commenting '@claude review'), link associated issues, and clean up the PR title and description. Ends with a readiness…
review-code
Standalone code review for any scope — PR number, branch, file paths, or current changes. Synthesizes intent, runs 11 parallel specialized agents, and presents actionable findings with a verdict. For PR scope, optionally posts the review to GitHub with inline comments.
review-converge
Autonomously review and fix the current branch or specified scope in iterative rounds until clean, leaving all changes in the working tree. Escalates only genuine design decisions. Ends with a transparent report of every round, every fix, and anything it couldn't resolve.
review-prs
Fetch and present a prioritized summary of all PRs awaiting the current user's review across the relevant projects and provide an interactive workflow helping the user phrase and post inline review comments and overall review decisions.
review-pr-comments-converge
Fetch PR review comments, validate each against the actual code, auto-fix obvious issues, and escalate genuine design decisions. Leaves all changes in the working tree. Use when you want to action reviewer feedback autonomously.
implement-unattended
Take a ticket whose approach and design are already approved through implementation, review and evidence to a draft PR, with nobody watching. Escalates decisions on the ticket and stops rather than choosing.