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Found 93 Skills
Think through ideas, investigate problems, and clarify requirements before committing to a change using `/opsx:explore`. Use when the user says "explore an idea", "think through this", "investigate options", or wants to brainstorm before creating a formal change.
Generate a persistent .nexus-map/ knowledge base that lets any AI session instantly understand a codebase's architecture, systems, dependencies, and change hotspots. Use when starting work on an unfamiliar repository, onboarding with AI-assisted context, preparing for a major refactoring initiative, or enabling reliable cold-start AI sessions across a team. Produces INDEX.md, systems.md, concept_model.json, git_forensics.md and more. Requires shell execution and Python 3.10+. For ad-hoc file queries or instant impact analysis during active development, use nexus-query instead.
This skill should be used when the user asks to "create an implementation plan", "plan a feature", "create detailed plan", "analyze requirements", or needs comprehensive project planning with requirements gathering and architectural analysis.
Generate project documentation from codebase analysis — ARCHITECTURE.md, API_ENDPOINTS.md, DATABASE_SCHEMA.md. Reads source code, schema files, routes, and config to produce accurate, structured docs. Use when starting a project, onboarding contributors, or when docs are missing or stale. Triggers: 'generate docs', 'document architecture', 'create api docs', 'document schema', 'project documentation', 'write architecture doc'.
Launch the interactive web dashboard to visualize a codebase's knowledge graph
Analyze codebases from the bottom up and generate a hierarchical README.md document tree. Start analysis from leaf directories, generate README.md files for each directory containing one-sentence descriptions of files, classes, and functions, and summarize layer by layer upwards to form a complete codebase documentation system. Supports state persistence and resumable analysis, suitable for scenarios such as understanding new projects, generating technical documentation, and analyzing code structures. Use this skill when you need to understand codebase structures, analyze function implementations, or generate code documentation.
Deep codebase analysis to generate 8 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.
Retrieve and explore DeepWiki-generated documentation for public GitHub repositories. Use when listing repository documentation topics, reading DeepWiki pages, or asking focused questions about a codebase that needs current repository structure, architecture notes, or component explanations.
Codebase analysis tool for quality-first editing. Scan before edit to understand relationships, patterns, and impact.
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.
This skill should be used when analyzing codebases, understanding architecture, or when "analyze", "investigate", "explore code", or "understand architecture" are mentioned.
Use when you need a fast, reliable architecture or impact view in a large unfamiliar repo, especially under time pressure or tight context budgets where manual grep or folder inference would be risky.