Borrowing it
Nothing to install: this file belongs to mick-gsk/drift. 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/mick-gsk/drift/main/.github/skills/drift-pr-review/SKILL.mdgit clone --depth 1 https://github.com/mick-gsk/driftWrote 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/mick-gsk/drift/drift-pr-review)<a href="https://agentmods.dev/skills/mick-gsk/drift/drift-pr-review"><img src="https://agentmods.dev/badge/skills/mick-gsk/drift/drift-pr-review/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/mick-gsk/drift/drift-pr-review"><img src="https://agentmods.dev/badge/skills/mick-gsk/drift/drift-pr-review.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00032 | $0.00844 |
| Opus 5 | $0.00016 | $0.00422 |
| Sonnet 5 | $0.00006 | $0.00169 |
| Haiku 4.5 | $0.00003 | $0.00084 |
Grade A, and why
drift-pr-review 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 10d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Drift PR Review Skill
Purpose
Guide Copilot agents through a policy-conformant, evidence-based pull request review for the drift repository.
When to Use
- Reviewing PRs that change
src/drift/,tests/, ordocs-site/ - Evaluating signal quality, scoring changes, or output format changes
- Checking benchmark evidence for new features
Strukturierte Review-Checkliste
Pflicht-Referenz: Die vollständige Review-Checkliste liegt unter .github/prompts/_partials/review-checkliste.md.
Bei jedem adversarialen Review wird diese Checkliste Punkt für Punkt abgearbeitet.
Der Reviewer dokumentiert pro Punkt Ja / Nein / N/A mit Kurzbegründung.
Review Workflow
Step 1: Policy Gate
Before reviewing code, verify the PR passes the Policy Gate:
### Drift Policy Gate
- Aufgabe: [PR title / description]
- Zulassungskriterium erfüllt: [JA / NEIN] → [which criterion]
- Ausschlusskriterium ausgelöst: [JA / NEIN] → [if YES: which]
- Roadmap-Phase: [1 / 2 / 3 / 4] — blockiert durch höhere Phase: [JA / NEIN]
- Entscheidung: [ZULÄSSIG / ABBRUCH]
- Begründung: [one sentence]
If the gate fails, comment with the reason and suggest what should be prioritized instead.
Step 2: Signal Quality Checklist
For every new or modified finding/signal, verify all 5 mandatory elements:
- Technical traceability — finding points to specific code location
- Reproducibility — finding can be reproduced from the same input
- Unique cause attribution — finding maps to exactly one root cause
- Clear justification — rationale is documented and understandable
- Actionable next step — a concrete remediation or investigation step exists
A finding missing any element is non-compliant with Policy §13.
Step 3: Benchmark Evidence
For feature PRs (feat: commits), verify:
-
benchmark_results/v*_feature_evidence.jsonartifact exists - Self-analysis score is equal or better than baseline
- No regression in precision/recall on known test repos
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.
- 10d ago First seen · 103 lines · 32 tokens per session scan A 04f244806fc1
drift-pr-review is a skill published in the GitHub repository mick-gsk/drift (15 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 844 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 2026-08-30.
Other skills, from other repositories
argot-setup
Set argot up for a repository end to end — audit its history, decide what should shape its voice, fit, verify the fit actually catches things, tune the rules its own history says are noisy, and wire the places it runs (pre-write hook, pre-commit, MCP, CI). One sitting, one decision at a time, each proposed with the…
pull-request-automation
Audits and improves the pull request workflow for a GitHub repository. Covers PR description templates, auto-labelling, CODEOWNERS, PR size checks, and branch protection rules. Invoked when the user asks to improve the PR process, set up PR automation, or add a PR template.
umbra-trust-review
Verify AI-generated code before shipping. Run Umbra's Trust Score scan before committing or finishing any coding task, treat findings as blocking issues, and re-scan until clean. Use when finishing a task, before a commit, or when reviewing code written by an agent.
ai-debt-audit
Scan a repository for AI-generated technical, cognitive, and intent debt. Use when the user asks to audit a codebase for AI/vibe-coding risk, check for issues an AI coding assistant may have introduced (disabled RLS, hardcoded secrets, missing auth checks, SSTI, debug mode left on), assess technical debt after heavy…
gh-find-prs
Survey open Codewhale PRs and triage each for mergeability and disposition against the real landing branch.
hunk-release
Prepares, publishes, verifies, and curates Hunk releases. Use for release metadata, benchmarks, tags, publishing, release videos, backports, or recovery.