Skills de Claude Code · página 94

Use when you have a spec or requirements for a multi-step task, before touching code

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

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Common agent patterns and templates for Claude Code. Use when implementing agents to follow proven patterns for Tasks integration, quality checks, and external model invocation via claudish CLI.

YAML frontmatter schemas for Claude Code agents and commands. Use when creating or validating agent/command files.

XML tag structure patterns for Claude Code agents and commands. Use when designing or implementing agents to ensure proper XML structure following Anthropic best practices.

YAML format for Claude Code agent definitions as alternative to markdown. Use when creating agents with YAML, converting markdown agents to YAML, or validating YAML agent schemas. Trigger keywords - "YAML agent", "agent YAML", "YAML format", "agent schema", "YAML definition", "convert to YAML".

Linear API patterns and examples for autopilot. Includes authentication, webhooks, issue CRUD, state transitions, file attachments, and comment handling.

Proof artifact generation patterns for task validation. Covers screenshots, test results, deployments, and confidence scoring.

Task lifecycle state transitions with validation gates. Defines states, triggers, and required proofs.

How tag-to-command routing works in autopilot. Defines default mappings, precedence rules, and customization patterns.

CRITICAL - Guide for using Claudish CLI ONLY through sub-agents to run Claude Code with OpenRouter models (Grok, GPT-5, Gemini, MiniMax). NEVER run Claudish directly in main context unless user explicitly requests it. Use when user mentions external AI models, Claudish, OpenRouter, or alternative models. Includes mandatory sub-agent delegation patterns, agent selection guide, file-based instructions, and strict rules to prevent context window pollution.

Use when analyzing architecture and system design. Find design patterns, map layers, identify core abstractions via PageRank. Uses claudemem AST structural analysis for efficient architecture investigation.

Use when orchestrating multi-agent code analysis with claudemem. Run claudemem once, share output across parallel agents. Enables parallel investigation, consensus analysis, and role-based command mapping.

⚡ PRIMARY TOOL for semantic code search AND structural analysis. NEW: AST tree navigation with map, symbol, callers, callees, context commands. PageRank ranking. Recommended workflow: Map structure first, then search semantically, analyze callers before modifying.

💡 Tool selector for code search tasks. Helps choose between semantic search (claudemem) and native tools (Grep/Glob) based on query type. Semantic search recommended for: 'how does X work', 'find all', 'audit', 'investigate', 'architecture'.

Use when integrating detective skills across plugins. Maps agent roles to appropriate detective skills (developer → developer-detective, architect → architect-detective). Reference this to connect agents with claudemem investigation capabilities.

⚡ Debugging skill. Best for: 'why is X broken', 'find bug source', 'root cause analysis', 'trace error', 'debug issue'. Uses claudemem AST with context command for efficient call chain analysis.

⚡ PRIMARY SKILL for: 'how does X work', 'investigate', 'analyze architecture', 'trace flow', 'find implementations'. PREREQUISITE: code-search-selector must validate tool choice. Launches codebase-detective with claudemem INDEXED MEMORY.

⚡ Implementation analysis skill. Best for: 'how does X work', 'find implementation of', 'trace data flow', 'where is X defined', 'find all usages'. Uses claudemem AST with callers/callees for efficient code tracing.

Unified entry point for code investigation. Auto-routes to specialized detective based on query keywords. Use when investigation type is unclear or for general exploration.

💡 Bulk file read optimizer. Suggests semantic search alternatives when reading multiple files. Helps reduce token usage by using claudemem's ranked results instead of sequential file reads.

⚡ Test analysis skill. Best for: 'what's tested', 'find test coverage', 'audit test quality', 'missing tests', 'edge cases'. Uses claudemem AST with callers analysis for efficient test discovery.

⚡ Comprehensive analysis skill. Best for: 'comprehensive audit', 'deep analysis', 'full codebase review', 'multi-perspective investigation', 'complex questions'. Combines all perspectives (architect+developer+tester+debugger). Uses Opus model with full claudemem AST analysis.

Get help with Conductor - commands, usage examples, and best practices

Execute tasks from track plan with TDD workflow and git commit integration

Create development track with spec and hierarchical plan through interactive Q&A

Git-aware logical undo at track, phase, or task level with confirmation gates

Initialize Conductor with product.md, tech-stack.md, and workflow.md

Show active tracks, progress, current tasks, and blockers

Architecture Decision Records (ADR) documentation practice. Use when documenting architectural decisions, recording technical trade-offs, creating decision logs, or establishing architectural patterns. Trigger keywords - "ADR", "architecture decision", "decision record", "trade-offs", "architectural decision", "decision log".

On-demand security and code quality audit. Use when checking for vulnerabilities, security issues, code smells, or compliance problems. Trigger keywords - "audit", "security check", "vulnerability scan", "code quality", "compliance", "security audit".

Use when designing REST or GraphQL APIs, defining endpoints, implementing pagination/filtering, handling API versioning, or establishing API documentation with OpenAPI/Swagger.

Use when implementing authentication (JWT, sessions, OAuth), authorization (RBAC, ABAC), password hashing, MFA, or security best practices for backend services.

Use when creating OpenAPI specs for Bun.js APIs, integrating with Apidog, documenting endpoints with schemas, or automating API specification imports via Apidog REST API. See bunjs for basics.

Use when implementing clean architecture (routes/controllers/services/repositories), establishing camelCase conventions, designing Prisma schemas, or planning structured workflows for Bun.js applications. See bunjs for basics, bunjs-production for deployment.

Use when deploying Bun.js to production, containerizing with Docker, setting up AWS ECS/Fargate, implementing Redis caching, hardening security, or configuring CI/CD pipelines. See bunjs for basics, bunjs-architecture for patterns.

Use when building Bun.js/Hono applications, implementing HTTP endpoints, setting up Prisma/SQLite, writing Zod validation, or using Bun's test runner. See bunjs-architecture for layered patterns, bunjs-production for deployment.

Use when designing database schemas, implementing repository patterns, writing optimized queries, managing migrations, or working with indexes and transactions for SQL/NoSQL databases.

Use when working with Dingo meta-language for Go, implementing optionals/results, using generics shortcuts, or transpiling .dingo files to .go while maintaining Go compatibility.

Use when implementing custom error classes, error middleware, structured logging, retry logic, or graceful shutdown patterns in backend applications.

Use when profiling Go applications (pprof), running benchmarks, optimizing memory/CPU usage, or debugging performance bottlenecks in production Go code.

Use when building Go backend services, implementing goroutines/channels, handling errors idiomatically, writing tests with testify, or following Go best practices for APIs/CLI tools.

Use when building FastAPI applications, implementing async endpoints, setting up Pydantic schemas, working with SQLAlchemy, or writing pytest tests for Python backend services.

Use when building Axum applications, implementing type-safe handlers, working with SQLx, setting up error handling with thiserror, or writing Rust backend services.

Use when detecting project technology stack from files/configs/directory structure, auto-loading framework-specific skills, or analyzing multi-stack fullstack projects (e.g., React + Go).

Use when troubleshooting bugs, analyzing stack traces, using debugging tools (breakpoints, loggers), or applying systematic debugging methodology across any technology stack.

Use when writing tests, setting up test frameworks, implementing mocking strategies, or establishing testing best practices (unit, integration, E2E) across any technology stack.

Use when implementing language-agnostic patterns like layered architecture, dependency injection, error handling, or code organization principles across any technology stack.

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Use when deciding whether to launch an agent, selecting which agent to use, or coordinating multiple agents. Covers delegation criteria, external-model patterns, task isolation, and agent selection strategies.

Use when debugging failures, errors, or unexpected behavior. Covers root cause investigation, data flow tracing, hypothesis-driven debugging, and fix verification to prevent trial-and-error approaches.

Use when writing production code. Enforces RED-GREEN-REFACTOR cycle: write failing test, make it pass, improve design. Prevents test-after development and ensures verified behavior.

Use when claiming task completion or marking items as done. Covers completion evidence requirements, verification methods, and anti-rationalization patterns.

Use when starting isolated feature work or before executing implementation plans. Manages full worktree lifecycle from creation through cleanup with safety checks and error recovery.

Use when writing README files, API documentation, user guides, or technical documentation following industry standards from Google, Microsoft, and GitLab style guides.

Evidence-based phase completion enforcement for /dev:feature. Use when orchestrating 8-phase feature development to ensure artifacts exist before phase completion, validation criteria are addressed, outer loops are enforced, and show-your-work requirements are met.

Systematically tests UI functionality, validates design fidelity with AI visual analysis, monitors console output, tracks network requests, and provides debugging reports using Chrome Extension MCP tools. Use after implementing UI features, for design validation, when investigating console errors, for regression testing, or when user mentions testing, browser bugs, console errors, or UI verification.

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Modern React 19+ patterns with TypeScript including function components, hooks, state management, TanStack Query integration, form handling with Zod, error boundaries, and performance optimization. Use when building React applications, implementing components, or setting up state management.

shadcn/ui component library patterns. Covers CLI usage, installation, component categories, theming with CSS variables, dark mode setup, and integration with React Hook Form + Zod. Use when adding UI components, setting up design systems, or implementing forms with shadcn/ui.

Use when choosing state management solutions, implementing global stores (Zustand, Pinia), managing server state (TanStack Query), or handling URL state in frontend applications across React and Vue.

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Comprehensive TanStack Query v5 patterns for async state management. Covers breaking changes, query key factories, data transformation, mutations, optimistic updates, authentication, testing with MSW, and anti-patterns. Use for all server state management, data fetching, and cache invalidation tasks.

TanStack Router patterns for type-safe, file-based routing. Covers installation, route configuration, typed params/search, layouts, and navigation. Use when setting up routes, implementing navigation, or configuring route loaders.

Use when writing component tests, testing user interactions, mocking APIs, or setting up Vitest/React Testing Library/Vue Test Utils for frontend applications.

Use when building Vue 3 applications with TypeScript, implementing Composition API components, setting up Pinia stores, or working with Vue Router. Covers script setup, composables, and reactive state.

MCP server standardization patterns for Claude Code plugins. Use when implementing MCP servers, designing tool interfaces, configuring MCP transports, or standardizing MCP naming conventions. Trigger keywords - "MCP", "MCP server", "MCP tools", "MCP transport", "tool naming", "MCP configuration".

On-demand performance and optimization analysis. Use when identifying bottlenecks, improving build times, reducing bundle size, or optimizing code performance. Trigger keywords - "optimize", "performance", "bottleneck", "bundle size", "build time", "speed up".

Collaborative ideation and planning with resilient multi-model exploration, consensus scoring, and adaptive confidence-based validation

Unified patterns and templates for creating consistent Claude Code plugins. Use when creating new plugins, designing plugin architecture, implementing builder patterns, or standardizing plugin structure. Trigger keywords - "plugin SDK", "plugin template", "plugin pattern", "builder pattern", "plugin structure", "new plugin", "plugin architecture".

Use BEFORE delegating any complex task to a subagent. Contains the routing table that maps task patterns to the correct specialized agent. MUST be consulted before using the Task tool for delegation decisions. Trigger keywords - "delegate", "subagent", "agent", "research", "implement", "investigate", "debug", "architect".

On-demand test coverage analysis. Use when identifying untested code, finding test gaps, measuring coverage metrics, or improving test quality. Trigger keywords - "test coverage", "coverage report", "untested code", "test gaps", "missing tests", "coverage metrics".

Use when integrating Apidog + OpenAPI specifications with your React app. Covers MCP server setup, type generation, and query layer integration. Use when setting up API clients, generating types from OpenAPI, or integrating with Apidog MCP.

Analyzes API documentation from OpenAPI specs to provide TypeScript interfaces, request/response formats, and implementation guidance. Use when implementing API integrations, debugging API errors (400, 401, 404), replacing mock APIs, verifying data types, or when user mentions endpoints, API calls, or backend integration.

Audit websites for SEO, technical, content, security, JS rendering, and AI readiness using SEOmator CLI. Returns LLM-optimized reports with health scores across 251 rules and 20 categories. Use when analyzing websites, debugging SEO issues, or checking site health.

Provides chunking strategies for RAG systems. Generates chunk size recommendations (256-1024 tokens), overlap percentages (10-20%), and semantic boundary detection methods. Validates semantic coherence and evaluates retrieval precision/recall metrics. Use when building retrieval-augmented generation systems, vector databases, or processing large documents.

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Implements document chunking, embedding generation, vector storage, and retrieval pipelines for Retrieval-Augmented Generation systems. Use when building RAG applications, creating document Q&A systems, or integrating AI with knowledge bases.

Provides AWS CloudFormation patterns for Auto Scaling including EC2, ECS, and Lambda. Use when creating Auto Scaling groups, launch configurations, launch templates, scaling policies, lifecycle hooks, and predictive scaling. Covers template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and best practices for high availability and cost optimization.

Provides AWS CloudFormation patterns for Amazon Bedrock resources including agents, knowledge bases, data sources, guardrails, prompts, flows, and inference profiles. Use when creating Bedrock agents with action groups, implementing RAG with knowledge bases, configuring vector stores, setting up content moderation guardrails, managing prompts, orchestrating workflows with flows, and configuring inference profiles for model optimization.

Provides AWS CloudFormation patterns for CloudFront distributions, origins (ALB, S3, Lambda@Edge, VPC Origins), CacheBehaviors, Functions, SecurityHeaders, parameters, Outputs and cross-stack references. Use when creating CloudFront distributions with CloudFormation, configuring multiple origins, implementing caching strategies, managing custom domains with ACM, configuring WAF, and optimizing performance.

Provides AWS CloudFormation patterns for CloudWatch monitoring, metrics, alarms, dashboards, logs, and observability. Use when creating CloudWatch metrics, alarms, dashboards, log groups, log subscriptions, anomaly detection, synthesized canaries, Application Signals, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and CloudWatch best practices for monitoring production infrastructure.

Provides AWS CloudFormation patterns for DynamoDB tables, GSIs, LSIs, auto-scaling, and streams. Use when creating DynamoDB tables with CloudFormation, configuring primary keys, local/global secondary indexes, capacity modes (on-demand/provisioned), point-in-time recovery, encryption, TTL, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references.

Provides AWS CloudFormation patterns for EC2 instances, Security Groups, IAM roles, and load balancers. Use when creating EC2 instances, SPOT instances, Security Groups, IAM roles for EC2, Application Load Balancers (ALB), Target Groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.

Provides AWS CloudFormation patterns for ECS clusters, task definitions, services, container definitions, auto scaling, blue/green deployments, CodeDeploy integration, ALB integration, service discovery, monitoring, logging, template structure, parameters, outputs, and cross-stack references. Use when creating ECS clusters with CloudFormation, configuring Fargate and EC2 launch types, implementing blue/green deployments, managing auto scaling, integrating with ALB and NLB, and implementing ECS best practices.

Provides AWS CloudFormation patterns for ElastiCache Redis or Memcached infrastructure, including subnet groups, parameter groups, security controls, and cross-stack outputs. Use when designing cache tiers, high-availability replication groups, encryption settings, or reusable CloudFormation templates for application caching.

Provides AWS CloudFormation patterns for IAM roles, policies, managed policies, permission boundaries, and trust relationships. Use when modeling least-privilege access, cross-account assumptions, service roles, or reusable IAM stacks that other CloudFormation templates consume.

Provides AWS CloudFormation patterns for Lambda functions, layers, API Gateway integration, event sources, cold start optimization, monitoring, logging, template validation, and deployment workflows. Use when creating Lambda functions with CloudFormation, configuring event sources, implementing cold start optimization, managing layers, integrating with API Gateway, and deploying Lambda infrastructure.

Provides AWS CloudFormation patterns for Amazon RDS databases. Use when creating RDS instances (MySQL, PostgreSQL, Aurora), DB clusters, multi-AZ deployments, parameter groups, subnet groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.

Provides AWS CloudFormation patterns for Amazon S3. Use when creating S3 buckets, policies, versioning, lifecycle rules, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.

Provides AWS CloudFormation patterns for security infrastructure including KMS encryption, Secrets Manager, IAM security, VPC security, ACM certificates, parameter security, outputs, and secure cross-stack references. Use when implementing security best practices, encrypting data, managing secrets, applying least privilege IAM policies, securing VPC configurations, managing TLS/SSL certificates, and implementing defense in depth strategies.

Provides patterns to deploy ECS tasks and services with GitHub Actions CI/CD. Use when building Docker images, pushing to ECR, updating ECS task definitions, deploying ECS services, integrating with CloudFormation stacks, configuring AWS OIDC authentication for GitHub Actions, and implementing production-ready container deployment pipelines. Supports ECS deployments with proper security (OIDC or IAM keys), multi-environment support, blue/green deployments, ECR private repositories with image scanning, and CloudFormation infrastructure updates.

Provides AWS CloudFormation patterns for VPC foundations, including subnets, route tables, internet and NAT gateways, endpoints, and reusable outputs. Use when creating a new network baseline, segmenting public and private workloads, or preparing CloudFormation networking stacks for application deployments.

Provides advanced AWS CLI patterns for managing EC2, Lambda, S3, DynamoDB, RDS, VPC, IAM, and CloudWatch. Generates bulk operation scripts, automates cross-service workflows, validates security configurations, and executes JMESPath queries for complex filtering. Triggers on "aws cli help", "aws command line", "aws scripting", "aws automation", "aws batch operations", "aws bulk operations", "aws cli pagination", "aws multi-region", "aws profiles", "aws cli troubleshooting".

Provides structured AWS cost optimization guidance using five pillars (right-sizing, elasticity, pricing models, storage optimization, monitoring) and twelve actionable best practices with executable AWS CLI examples. Use when optimizing AWS costs, reviewing AWS spending, finding unused AWS resources, implementing FinOps practices, reducing EC2/EBS/S3 bills, configuring AWS Budgets, or performing AWS Well-Architected cost reviews.