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Found 182 Skills
Recursive Language Models (RLM) CLI - enables LLMs to recursively process large contexts by decomposing inputs and calling themselves over parts. Use for code analysis, diff reviews, codebase exploration. Triggers on "rlm ask", "rlm complete", "rlm search", "rlm index".
Analyzes source code to automatically generate technical documentation and architecture diagrams. Use to maintain up-to-date API references and onboarding materials for engineering teams.
Generate an LLM-optimized project profile for any git repository. Outputs docs/{project-name}.md covering architecture, core abstractions, usage guide, design decisions, and recommendations. Trigger: "/project-profiler", "profile this project", "為專案建側寫"
IntelliJ-IDEA MCP provides powerful IDE features including running tests, code analysis, refactoring, search, and project navigation. Use this when you need accurate Java code analysis (avoiding LSP false positives), running tests via IDEA configurations, refactoring symbols, or exploring codebase structure. Key commands: execute_run_configuration (run tests), get_file_problems (accurate errors/warnings), search_in_files_by_text (search code), list_directory_tree (view structure), get_file_text_by_path (read files), rename_refactoring (safe refactoring), execute_terminal_command (run shell commands).
Conducts multi-turn iterative deep research on specific topics within a codebase with zero tolerance for shallow analysis. Use when the user wants an in-depth investigation, needs to understand how...
Use when analyzing repositories, conducting deep research on codebases, performing architecture reviews, or exploring large projects. Use when the user wants to research or analyze a git repo, a GitHub link, or a repository URL.
Maps questions to the optimal tldr command. Use this to pick the right layer
Check reference SDK implementations using btca ask
Token-efficient code analysis via 5-layer stack (AST, Call Graph, CFG, DFG, PDG). 95% token savings.
Scan codebase for security vulnerabilities including secrets, insecure dependencies, and unsafe code patterns. Use when performing automated security scans.
Worker that checks DRY/KISS/YAGNI/architecture compliance with quantitative Code Quality Score. Validates architectural decisions via MCP Ref: (1) Optimality (2) Compliance (3) Performance. Reports issues with SEC-, PERF-, MNT-, ARCH-, BP-, OPT- prefixes.
Repository packaging for AI/LLM analysis. Capabilities: pack repos into single files, generate AI-friendly context, codebase snapshots, security audit prep, filter/exclude patterns, token counting, multiple output formats. Actions: pack, generate, export, analyze repositories for LLMs. Keywords: Repomix, repository packaging, LLM context, AI analysis, codebase snapshot, Claude context, ChatGPT context, Gemini context, code packaging, token count, file filtering, security audit, third-party library analysis, context window, single file output. Use when: packaging codebases for AI, generating LLM context, creating codebase snapshots, analyzing third-party libraries, preparing security audits, feeding repos to Claude/ChatGPT/Gemini.