repomix
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.
AILANG Debug
Debug AILANG code errors. Use when you encounter type errors, parse errors, or runtime failures in AILANG programs.
repomix
Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases. | Sử dụng khi: đóng gói repo, pack codebase, context cho AI.
deep-wiki
Access AI-generated documentation and insights for GitHub repositories via DeepWiki. This skill should be used when exploring unfamiliar codebases, understanding repository architecture, finding implementation patterns, or asking questions about how a GitHub project works. Supports any public GitHub repository.
gkg
Global Knowledge Graph for codebase analysis. This skill should be used when searching for code definitions (functions, classes, methods), finding references to symbols, understanding code structure, analyzing import usage, generating repository maps, or performing impact analysis before refactoring. Supports TypeScript, JavaScript, Python, Java, and more.
code-profiler
Use when asked to profile Python code performance, identify bottlenecks, measure execution time, or analyze function call statistics.
aboutme-index
Index-based file discovery using ABOUTME headers. Use INSTEAD of grep or Explore agent when searching for files by purpose or feature. Faster and more accurate than scanning code. Invoke this skill when user asks "which files handle X", "where is Y implemented", or when you need to find files related to a feature or task.
spec-coverage-map
Generate a visual spec-to-code coverage map showing which code files are covered by which specifications. Creates ASCII diagrams, reverse indexes, and coverage statistics. Use after implementation or during cleanup to validate spec coverage.
analyze
Perform initial analysis of a codebase - detect tech stack, directory structure, and completeness. This is Step 1 of the 6-step reverse engineering process that transforms incomplete applications into spec-driven codebases. Automatically detects programming languages, frameworks, architecture patterns, and generates comprehensive analysis-report.md. Use when starting reverse engineering on any codebase.
reverse-engineer
Deep codebase analysis to generate 9 comprehensive documentation files. Adapts based on path choice - Greenfield extracts business logic only (tech-agnostic), Brownfield extracts business logic + technical implementation (tech-prescriptive). This is Step 2 of 6 in the reverse engineering process.
repo-clipboard
Snapshot the current directory into pseudo-XML for LLM context. Use when you need to share a repo (or a sub-tree) with Codex/LLMs, especially for code review/debugging, generating an agent-friendly “repo snapshot”, or piping context into tools like `llm` (see skill $llm-cli). Supports `.gitignore`-aware file discovery, common ignore patterns, extension filtering, regex include/exclude, optional file-list printing, line-range snippets, and writes `/tmp/repo_clipboard.{stdout,stderr}` for reuse.
explore-codebase
Autonomously explore unfamiliar codebases using Julie's code intelligence. Use semantic search, symbol navigation, and call path tracing to understand architecture without reading entire files. Activates when user asks to understand, explore, or learn about a codebase.
semantic-intelligence
Use Julie's semantic search capabilities for conceptual code understanding. Activates when searching for concepts, cross-language patterns, business logic, or exploring unfamiliar code. Combines text and semantic search for optimal results.
safe-refactor
Perform safe code refactoring with reference checking and validation. Uses Julie's rename_symbol for workspace-wide renames and fuzzy_replace for precise edits. Activates when user wants to refactor, rename, or safely modify code.
smart-search
Intelligently choose between semantic and text search based on query intent. Automatically selects the best search mode (semantic for concepts, text for exact terms, symbols for definitions) and provides relevant results. Use when user wants to find code.
cl-coding-style
Common Lispのコーディング規約を適用。Lispコード作成・レビュー時に使用
cl-mallet-linter
malletリンターのルールと設定を適用。コードレビュー・品質チェック時に使用
twist-nix-nav
Navigate a local emacs-twist/twist.nix checkout and point to relevant files for questions about twist.nix configuration, flake outputs, library functions, Home Manager integration, package build flow, or tests. Use when a user asks where something is defined or how twist.nix is wired and the answer should reference code rather than reproduce it. Ask for the repo path if it is not available.
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