Überprüft ein Pull-Request-Diff und schreibt strukturiertes Feedback in review.json, damit der Workflow es veröffentlichen kann. Verwenden Sie es, wenn Sie einen ausgecheckten PR aus lokalen Artefakten wie pr_diff.txt und pr_description.txt überprüfen und maschinenlesbare Überprüfungsergebnisse anstelle einer direkten Veröffentlichung auf GitHub erstellen.
Der Skill `warpdotdev/review-pr` ermöglicht es einem KI-Agenten, einen Pull-Request-Diff zu überprüfen und strukturiertes Feedback in eine `review.json`-Datei zu schreiben. Dieses maschinenlesbare Format ist für nachgelagerte Workflows optimiert, anstatt direkt auf GitHub zu veröffentlichen. Er wird typischerweise in CI/CD-Umgebungen oder lokalen Entwicklungsszenarien eingesetzt, bei denen ein PR bereits ausgecheckt und als lokale Artefakte wie `pr_diff.txt` und `pr_description.txt` verfügbar ist. Der Skill ist besonders nützlich, um Code-Reviews zu automatisieren und konsistente, strukturierte Ergebnisse für weitere Automatisierungsschritte bereitzustellen. Er unterstützt eine präzise und effiziente Integration in Entwickler-Workflows, da er die Überprüfungsergebnisse in einem standardisierten JSON-Format ablegt, das von anderen Tools weiterverarbeitet werden kann.
npx skills add https://github.com/warpdotdev/common-skills/tree/main/skills/review-prInstalled? Explore more Produktivität & Zusammenarbeit skills: steipete/gemini, steipete/gh-issues, steipete/skill-creator · View all 6 →
Überprüfen Sie ein Pull-Request-Diff und schreiben Sie strukturiertes Feedback in review.json, damit der Workflow es veröffentlichen kann. Verwenden Sie es, wenn Sie einen ausgecheckten PR aus lokalen Artefakten wie pr_diff.txt und pr_description.txt überprüfen und maschinenlesbare Überprüfungsergebnisse anstelle einer direkten Veröffentlichung auf GitHub erstellen.
This repo contains 16 individual skills — each has its own dedicated page.
Guides creation, revision, and review of Warp- or Oz-branded assets. Use when working on launch pages, docs, HTML/CSS components, UI mockups, prompts, social assets, copy, presentations, or any other branded deliverable that should look and sound unmistakably Warp or Oz.
Compare a pull request's implementation against spec context in spec_context.md and feed any material mismatches into review.json. Use during PR review when approved or repository spec context is available.
Run a model-diverse subagent council to investigate the same problem from multiple perspectives, compare findings, and produce a final recommendation. Use this skill whenever the user asks for a council, second opinions, multiple agents/models to evaluate one question, parallel investigation, red-team/blue-team comparison, or help deciding between competing technical approaches.
Create a pull request in the warp repository for the current branch. Use when the user mentions opening a PR, creating a pull request, submitting changes for review, or preparing code for merge.
Diagnose CI failures for a PR using the GitHub CLI, extract error logs, and generate a plan to fix them. Use when the user asks to check CI status, pull CI issues, triage test failures, or investigate PR build failures.
Fix compilation errors, linting issues, and test failures in the warp Rust codebase. Covers presubmit checks, WASM-specific errors, and running specific tests. Use when the user hits build errors, clippy or fmt failures, test failures, or needs to run or interpret presubmit before a PR.
Implement an approved feature from PRODUCT.md and TECH.md, keeping specs and code aligned in the same PR as implementation evolves. Use after the product and tech specs are approved and the next step is building the feature.
Generate a static interactive D3 walkthrough of a pull request. Use when the user wants a zoomable PR map, graph/canvas PR orientation, or alternate visualization of PR system components, data flow, code dependencies, and user actions.
Launch Oz cloud agents with computer use to reproduce UI-focused bug reports, capture visual evidence, and report reproduction findings. Use when investigating a specific interactive or visual bug from an issue, ticket, support report, or prompt.
Resolve Git merge conflicts by extracting only unresolved paths, conflict hunks, and compact diffs instead of loading whole files into context. Use when a merge, rebase, cherry-pick, or stash pop stops on conflicts, when `git status` shows unmerged paths, or when files contain conflict markers.
Walk users through PR review comments, fetching and displaying them first when needed, collect per-comment response decisions, apply requested fixes, and preview GitHub replies and resolutions before posting. Use when responding to PR review comments on the current branch.
Drive a spec-first workflow for substantial features by writing PRODUCT.md before implementation, writing TECH.md when warranted, and keeping both specs updated as implementation evolves. Use when starting a significant feature, planning agent-driven implementation, or when the user wants product and tech specs checked into source control.
Create or update skills by generating, editing, or refining SKILL.md files in this repository. Use when authoring new skills or revising the structure, frontmatter, or guidance for existing ones.
Validate that a branch or pull request implementation matches introduced product, technical, security, and related specs. Use when reviewing or finishing a spec-driven change and resolving mismatches between checked-in specs and implementation.
Write a PRODUCT.md spec for a significant user-facing feature in Warp, focused on detailed behavior and validation. Use when the user asks for a product spec, desired behavior doc, or PRD, wants to define feature behavior before implementation, or when the feature is substantial or behaviorally ambiguous enough that a written spec would improve implementation or review.
Write a TECH.md spec for a significant Warp feature after researching the current codebase and implementation constraints. Use when the user asks for a technical spec, implementation plan, or architecture doc tied to a product spec.
Gemini CLI one-shot prompts, summaries, generation, skills, hooks, MCP, or Gemma routing.
Fetch GitHub issues, select candidates, spawn background fix agents, open PRs, and optionally process PR review comments.
Create, edit, audit, tidy, validate, or restructure AgentSkills and SKILL.md files.
Search, install, update, sync, or publish agent skills with the ClawHub CLI and registry.
Delegate coding work to Codex, Claude Code, or OpenCode as background workers; not simple edits or read-only code lookup.
List, configure, authenticate, call, and inspect MCP servers/tools with mcporter over HTTP or stdio.