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Found 140 Skills
Comprehensive technology-agnostic prompt generator for documenting end-to-end application workflows. Automatically detects project architecture patterns, technology stacks, and data flow patterns to generate detailed implementation blueprints covering entry points, service layers, data access, error handling, and testing approaches across multiple technologies including .NET, Java/Spring, React, and microservices architectures.
Transform codebases into authentic, interview-defensible resume project experience. Use when analyzing a codebase for: (1) Extracting resume-ready project descriptions, (2) Preparing for technical interview questions about past projects, (3) Understanding the engineering depth and value of a codebase, (4) Identifying defensible technical achievements. Prioritizes correctness and interview credibility over exaggeration.
[Docs] ⚡⚡⚡⚡ Analyze the codebase and create initial documentation
Discover and document business rules, technical patterns, and system interfaces through iterative analysis
Manages persistent Knowledge Graph for specifications. Caches agent discoveries and codebase analysis to remember findings across sessions. Validates task dependencies, stores patterns, components, and APIs to avoid redundant exploration. Use when: you need to cache analysis results, remember findings, reuse previous discoveries, look up what we found, spec-to-tasks needs to persist codebase analysis, task-implementation needs to validate contracts, or any command needs to query existing patterns/components/APIs.
Transform legacy codebases into AI-ready projects with Claude Code configurations. Use when (1) analyzing old projects to generate AI coding configurations, (2) creating CLAUDE.md, skills, subagents, slash commands, hooks, or rules for existing projects, (3) user wants to enable vibe coding for a codebase, (4) onboarding new team members with AI-assisted development, (5) user mentions "make project AI-ready", "generate Claude config", or "create coding standards for AI".
Generate hierarchical AGENTS.md structures for codebases. Use when user asks to create AGENTS.md files, analyze codebase for AI agent documentation, set up AI-friendly project documentation, or generate context files for AI coding assistants. Triggers on "create AGENTS.md", "generate agents", "analyze codebase for AI", "AI documentation setup", "hierarchical agents".
Based on the Recursive Language Models (RLM) research by Zhang, Kraska, and Khattab (2025), this skill provides strategies for handling tasks that exceed comfortable context limits through programmatic decomposition and recursive self-invocation. Triggers on phrases like "analyze all files", "process this large document", "aggregate information from", "search across the codebase", or tasks involving 10+ files or 50k+ tokens.
Update and maintain CLAUDE.md and README.md documentation
Analyze a GitHub codebase to create comprehensive architecture documentation including ASCII diagrams, component relationships, data flow, hosting infrastructure, and file structure assessment.
Review a spec document against codebase reality, identifying gaps and ensuring sound, robust implementations.
CLAUDE.md file generation and optimization for Claude Code projects. Capabilities: initialize project instructions, analyze codebase context, optimize existing CLAUDE.md, apply Anthropic best practices, reduce token usage, improve effectiveness. Actions: init, create, optimize, enhance CLAUDE.md files. Keywords: CLAUDE.md, project instructions, Claude Code setup, project context, codebase analysis, Anthropic best practices, token optimization, project configuration, AI instructions, coding guidelines, project rules, workspace setup. Use when: initializing CLAUDE.md for new projects, optimizing existing project instructions, setting up Claude Code for a codebase, improving AI coding guidelines.