编码规范、框架、重构、代码审查（1.8万 个）
Build the core Tool and Resource pattern for MCP Apps: connect tools to UI resources, pass structured data to the interface, and provide text responses for hosts without UI support. Includes app-only helper tools and shared resources.
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Configure Vite to bundle an MCP App as one self-contained HTML file, inlining JavaScript, CSS, images, and fonts for use in a sandboxed iframe. Set up entry points and build scripts, including separate UI and server build phases.
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Match a dynamic programming problem to a known pattern, then get guidance on states, transitions, variants, and optimizations. Generate commented Python, C++, or Java templates, including space-optimized versions, to help turn a recognized approach into code.
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Guides the creation and editing of agent skill documents and checks whether they work before deployment. It uses pressure scenarios with subagents to see whether a skill changes agent behavior, then refines the document to close gaps.
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Design modular LangGraph workflows by building reusable subgraphs and composing them into larger graphs. Handle state mapping, nested or parallel execution, clear component interfaces, and error boundaries between workflow parts.
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Add human review and approval points to LangGraph workflows. Configure when execution pauses, how workflows resume after input, and how pending approvals are handled through timeouts, escalation paths, and notifications.
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Turn a multi-step software specification into a practical implementation plan before coding. It breaks work into small tasks, tracks dependencies, and gives each task a test-first sequence with expected results and a handoff path for execution.
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Investigate bugs, failing tests, and unexpected behavior by tracing data flow, comparing working examples, and testing one hypothesis at a time. It guides a focused fix and verification, and prompts you to reconsider the architecture after repeated failed fixes.
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Use this skill to carry out implementation plans with independent tasks in the current session. It assigns a fresh subagent to each task and adds separate checkpoints for checking whether the work meets the request and whether the code is well built.
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Evaluate code review feedback against the actual codebase before making changes. Clarify the requirement, check technical fit, respond with acknowledgment or a reasoned objection, then implement valid suggestions one at a time.
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Build custom tools for LangChain agents and connect existing tools or APIs. Define structured inputs, descriptions, return types, and error handling so an LLM can understand how to call each tool; the skill also covers tool chains and pipelines.
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Decide what to do with a development branch after implementation is complete and tests pass. The workflow checks the base branch, presents four integration choices, carries out the selected option, and cleans up the worktree when required.
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Execute a written implementation plan in a separate session, handling tasks in batches and reporting for review between them. It supports resuming saved tasks, setting up a worktree, and finishing the branch after the plan is complete.
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Use this skill to split independent engineering problems across parallel agents. It helps coordinate separate investigations, check their solutions for conflicts, and verify the combined result with the full test suite.
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Turn a technical plan into small development tasks with acceptance criteria, effort estimates, dependencies, and links to specification requirements. The skill also identifies work that can happen in parallel, maps the critical path, and includes testing tasks.
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Convert feature requests into user-focused requirements and stories with testable acceptance criteria. The skill clarifies business value, scope, edge cases, assumptions, and open questions so a specification can be reviewed before planning.
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Carry out feature development from a specification by preparing project files, implementing tasks in dependency order, and checking acceptance criteria with tests. It also validates requirement coverage and includes integration testing and a human review step.
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Define and document project-wide principles for how a team works, including development practices, code quality, testing, UX, performance, security, and architecture. Use it to formalize existing standards or set governance before planning a new feature area.
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Compare project rules, specifications, plans, and tasks before implementation. This skill maps requirements to planned work, flags missing coverage and conflicting instructions, checks acceptance criteria, and reports whether the artifacts are consistent and ready for implementation.
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Request a code review after finishing work, implementing a major feature, or preparing to merge. The review checks the changes against requirements and returns feedback grouped by urgency, so you can address critical and important issues before proceeding.
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Clarify goals and requirements before coding begins. The process reviews project context, explores design options and tradeoffs, then prepares a design document for approval before implementation planning continues.
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Set up LangSmith tracing for LLM applications built with LangChain or LangGraph. Capture nested execution traces, inspect run history and metadata, and compare runs to help debug agent behavior. Requires a LangSmith account and API key.
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Sets up an isolated Git worktree and new branch for feature work, detects the project setup command, and checks the existing test baseline. It helps prepare a separate workspace before carrying out an implementation plan.
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Plan and work through complex coding tasks in stages, using tools, correcting mistakes, and checking the proposed solution. The source describes autonomous engagement without human intervention, but provides no implementation details beyond that overview.
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