编码规范、框架、重构、代码审查（1.5万 个）
Add an agent execution engine to gh-aw using a shared Markdown definition where possible. The skill guides installation, authentication, configuration, and testing, with Go infrastructure changes reserved for capabilities that existing settings cannot express.
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Follow gh-aw development conventions with checks matched to Go, JavaScript, and workflow changes. Provides staged validation commands, capitalization rules, and pointers to more detailed guidance for specific parts of the codebase.
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Use concrete JSON and Markdown examples to structure Sergo tool caches, strategy histories, improvement tasks, and reports. The templates show which fields to record and how to organize findings for review.
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Implement HTTP headers that pass GitHub Actions secrets through environment variables in gh-aw’s copilot engine. This reference explains secret extraction, generated MCP configuration, execution-step settings, and tests for keeping secret values out of configuration files.
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Retrieve labels from a GitHub repository, filter their names by partial matches, and choose page sizes and page numbers. Results arrive as JSON, including label names, colors, descriptions, and pagination details.
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Improve validation errors in gh-aw so users can see what went wrong, what input is expected, and how to fix it. Provides writing patterns, valid YAML examples, Go error-handling guidance, and checks for message quality.
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Find current Remotion documentation for a feature or API, then retrieve relevant pages as Markdown. Use the documented behavior to guide implementation instead of relying on previously learned API details.
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Update Remotion and its related packages while keeping their versions aligned. The workflow checks project dependencies, updates installed Remotion skills and lockfiles, and reviews changes using the project's existing package management conventions.
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Build apps with Remotion, from forms that trigger video rendering to complex video editors. Get guidance on templates, embedded previews, and choosing where rendering—the process of producing the video—runs.
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Check GitHub pull request review comments against the actual code. Classify findings as valid, invalid, or partially valid, identify similar issues elsewhere, and produce recommended actions, with optional replies after user approval.
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Use ccwf to validate workflow JSON files, preview their steps in a browser, and produce Mermaid flowcharts. Export workflows as skill files for supported agents, or generate the files and launch Claude Code to proceed with execution.
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Adjust how AI agents generate workflows in cc-wf-studio by reviewing node descriptions, examples, and misleading constraints. The skill guides minimal schema edits, format regeneration, and testing to address biased node choices.
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Prepare a pull request to main in the specified pnpm monorepo, where multiple packages share one repository. Identify affected packages, ensure Changesets release records are appropriate, run checks and builds, and write an English review submission.
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Advance one development task by managing an existing pull request, fixing a build failure or bug, or implementing a queued idea. Record the work and integrate changes into auto-dev only after automated checks pass.
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Turn previously retrieved Jira requirements and Confluence documents into a structured implementation plan. Tasks are grouped into frontend, backend, and infrastructure work, with architectural reasoning, blocking dependencies, and risks paired with mitigation measures.
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Develop user-visible improvements for cc-wf-studio, verify their basis in the code, and assess their value. Record qualifying proposals as locked GitHub issues, creating a queue of concrete ideas for later implementation without changing code.
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Clean up a feature branch after its pull request is merged into main. Switch to main, pull the latest changes, and delete both local and remote branches, including branches merged through a squash merge.
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Set up Zero and retrieve workflow guidance matched to the installed compiler. This skill helps agents load the references needed for editing, checking, and testing code, while preserving the compiler version already used by the project.
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Create, edit, and check mirrord.json files that connect a local application to Kubernetes. The skill produces minimal configurations, validates their structure and allowed settings, and explains problems with environment variables, files, and network behavior.
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Update application code so a developer’s mirrord session identifier travels across service calls, queues, and storage events. Reuse existing tracing tools where possible, then report which request flows carry the identifier and where it still disappears.
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Manage Python and R packages for notebook work. Resolve missing-package errors, check installed versions, install into the selected runtime, and restart the kernel when needed, with guidance on using separate environments for different dependency requirements.
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Turn a recurring task into a reusable Open-Science Skill, or revise an existing one. Guide package creation, optional testing, improvements to when the Skill activates, and publication after the user reviews and accepts the draft.
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Delegate a focused coding, research, review, or verification task to a separate DevSpace agent. Choose an available worker, provide a self-contained brief, inspect or wait for results, and continue related work with the same agent.
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Review changes to a multilingual source code parser, focusing on whether relationships between code elements are correct. Check consistency across languages and verify that test examples reproduce the issue and actually validate the fix.
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