Explora nuestra colección completa de Habilidades de Claude que extienden las capacidades de los agentes de IA.
Generates verified Mermaid-based system diagrams, ER models, and architecture visualizations by performing deep analysis of your actual codebase.
Orchestrates complex feature development using parallel subagents and automated quality verification gates.
Injects framework-specific best practices into CLAUDE.md to improve AI agent performance and reduce code hallucinations.
Search and retrieve context from historical Claude sessions to maintain continuity across projects and devices.
Defines actionable AI validation criteria and testing standards to ensure code quality before task completion.
Performs automated security audits and OWASP Top 10 compliance checks on pull requests, commits, or entire codebases.
Implements idiomatic Go testing patterns including table-driven tests, benchmarks, and fuzzing to ensure robust code quality.
Implements best practices for Spring Boot data persistence, query optimization, and entity modeling.
Styles applications using modern Tailwind CSS v4 utilities and CSS-first configuration patterns.
Configures AI model selection, cost estimates, and batch processing strategies for qualitative research workflows.
Automates the progression of development workflows by generating sequential OpenSpec artifacts from proposals to implementation tasks.
Executes multi-phase technical implementation plans with systematic automated verification and progress tracking.
Breaks down complex software projects into manageable, dependency-aware tasks with progress tracking and visual roadmaps.
Streamlines sprint planning by guiding users through brainstorming, task sizing, and automated backlog documentation for Claude Code.
Navigates complex research contradictions and integrates conflicting data patterns using contemplative reasoning frameworks.
Converts complex PDFs, academic papers, and tables into structured formats using intelligent tool selection and VLM-based parsing.
Facilitates structured, step-by-step thinking for complex analytical decisions and theoretical framework construction using the Sequential Thinking MCP.
Initializes qualitative research environments with structured epistemic foundations and standardized folder hierarchies.
Orchestrates systematic document coding, progress tracking, and audit trail generation for qualitative research projects.
Sets up a comprehensive Kanban-style sprint structure optimized for multi-agent collaboration and project tracking.
Resolves software defects through automated test-driven reproduction, root cause analysis, and rigorous regression verification.
Architects complex technical solutions by evaluating algorithms, data structures, and system boundaries to ensure robust implementation.
Automates the generation of accurate, data-driven standup reports by analyzing Jira ticket activity and local git commit history.
Automates the process of pushing changes and creating or updating GitHub Pull Requests using Jujutsu and the GitHub CLI.
Reviews completed project milestones and captures hard-won lessons to build organizational memory and improve future workflows.
Ensures methodological rigor in qualitative research by enforcing isolation rules and phase-aware guidance through specialized AI agents.
Generates intelligent daily work plans and ticket prioritization by analyzing live Jira data and developer context.
Automates high-fidelity PDF and document conversion by selecting the optimal parsing method for academic and qualitative research data.
Analyzes local code changes using parallel AI agents to automatically identify and fix bugs, type errors, and architectural complexity.
Automates iOS application development, testing, and UI interactions using integrated XcodeBuildMCP tools and multi-agent workflows.
Scroll for more results...