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Found 80 Skills
Generate feature specifications by analyzing existing source code.
Generate comprehensive scientific research-style documentation for completed coding projects. Use when the user requests project documentation, a technical breakdown, a study paper, a lecture document, or wants to understand everything about a project they just built. Triggers include phrases like "document this project," "create a study paper," "explain everything we did," "write up the full breakdown," "scientific documentation," or "I want to learn from this project." Produces formal Word documents (.docx) with academic structure, beginner-friendly explanations, and exhaustive code analysis.
Analyze brownfield codebase and create initial continuity ledger
Setup and workflow for using sqry semantic code search as an MCP server with OpenAI Codex CLI. Covers installation, MCP configuration via `~/.codex/config.toml`, and recommended patterns for code analysis tasks. Install this skill to give Codex access to sqry's 34 AST-based code analysis tools.
Analyze source code and produce an enterprise-quality, domain-organized Wiki under `.nium-wiki/`. Trigger on: "generate wiki", "create docs", "update wiki", "rebuild wiki", or any documentation generation request. Capabilities: - Semantic code analysis — understands logic, not just structure - Auto-generated Mermaid diagrams (architecture, data flow, class, dependency) - Bidirectional cross-linking across all documents - SHA256-based change detection for incremental rebuilds - Every section traces back to source via relative path links - Multi-language output (zh/en/ja/ko/fr/de and more)
Run Gemini CLI for AI-powered tasks, code understanding, file operations, and automation. Free tier with Google OAuth (included in Gemini Advanced). Use for fast generation, bulk content, debugging, and research. Preferred for load balancing sub-agent work (35% weight).
CLI tools execution specification (gemini/claude/codex/qwen/opencode) with unified prompt template, mode options, and auto-invoke triggers for code analysis and implementation tasks. Supports configurable CLI endpoints for analysis, write, and review modes.
Explores codebase with structural and text search using ast-grep (syntax-aware AST matching), ripgrep (fast text/regex search), and fd (file discovery). Use when (1) navigating unfamiliar code or understanding architecture, (2) tracing call flows, symbol definitions, or usages, (3) answering "how does this work" or "where is this defined/called" questions, (4) finding files by name, extension, or path pattern, (5) pre-refactoring analysis to locate all references before changing code.
Use when answering complex questions about a codebase that require exploring multiple areas or understanding how components connect - coordinates parallel sub-agents to locate, analyze, and synthesize findings
The Meta-Skill for managing standard capabilities. Use it to install, update, or list available standard skills (like auto-committer, context-code-explainer).
This skill MUST be used for semantic Rust navigation and analysis: resolving definitions across crate boundaries, finding all references to a symbol, inspecting inferred types or trait implementations, searching symbols by name, and renaming symbols safely. SHOULD be preferred over grep or file reads whenever the task requires Rust-aware understanding.
Official GitHub MCP Server for AI-powered repository management, issue/PR automation, CI/CD monitoring, and code analysis through natural language