Inicie agentes na nuvem Oz com uso de computador para reproduzir relatórios de bugs focados em UI, capturar evidências visuais e relatar descobertas de reprodução. Use ao investigar um bug interativo ou visual específico de uma issue, ticket, relatório de suporte ou prompt.
Esta skill permite que você lance agentes na nuvem Oz equipados com capacidade de uso de computador para reproduzir bugs focados em interface do usuário (UI). Ao fornecer um relatório de bug, ticket de suporte ou descrição de um problema visual ou interativo, a skill orquestra um agente autônomo que tenta replicar o bug em um ambiente controlado, captura screenshots ou gravações como evidência visual e compila um relatório detalhado das descobertas. É particularmente útil para desenvolvedores e testadores que precisam investigar e documentar bugs de forma sistemática, economizando tempo e garantindo consistência na reprodução. A skill suporta plataformas como Claude Code, Cursor e Codex, integrando-se perfeitamente ao fluxo de trabalho de desenvolvimento. Ela funciona processando a descrição do bug, simulando as interações do usuário e gerando um relatório com capturas de tela e passos reproduzidos.
npx skills add https://github.com/warpdotdev/common-skills/tree/main/skills/reproduce-bug-reportInstalled? Explore more Imagem skills: steipete/songsee, affaan-m/frontend-design, mattpocock/improve-codebase-architecture · View all 6 →
Inicie agentes na nuvem Oz com uso de computador para reproduzir relatórios de bugs focados em UI, capturar evidências visuais e relatar descobertas de reprodução. Use ao investigar um bug interativo ou visual específico de uma issue, ticket, relatório de suporte ou prompt.
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.
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.
Review a pull request diff and write structured feedback to review.json for the workflow to publish. Use when reviewing a checked-out PR from local artifacts like pr_diff.txt and pr_description.txt and producing machine-readable review output instead of posting directly to GitHub.
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.
Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.
Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
Add documentation for a new AI provider — usage docs, env vars, Docker config, image resources.
Tests in real browsers via Chrome DevTools MCP. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data. Requires the chrome-devtools MCP server to be configured.
This skill should be used when the user wants to visualize data. It intelligently selects the most suitable chart type from 26 available options, extracts parameters based on detailed specifications, and generates a chart image using a JavaScript script.