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Found 12 Skills
Use this when you need to evaluate the risks and benefits of accepting, negotiating before accepting, pausing, or rejecting outsourcing projects, internal projects, or requirements. It is particularly suitable for scenarios with ambiguity in scope, acceptance criteria, payment terms, compliance, project timelines, or dependencies, as well as high-uncertainty situations such as emergency task insertion, contract renewal/modification, multi-requirement prioritization, or AI/LLM-related initiatives.
Build features with AI coding tools (Claude Code, Lovable, Replit, Cursor). Use when implementing specs, iterating on AI code, or choosing tools. Focuses on tool selection, effective prompting, and iteration workflows for non-technical founders.
Help users build software using AI coding tools. Use when someone is using AI to generate code, building prototypes without deep technical skills, or exploring how non-engineers can create functional software through natural language.
Setup universal code quality standards in your project. Use when the user wants to generate coding standards files (CLAUDE.md, AGENTS.md, GEMINI.md, etc.) or mentions 'code standards', 'code review setup', or similar intent in any language.
Ouroboros specification-first AI development — the complete system. Socratic interviewing crystallizes vague ideas into immutable specs (Ambiguity ≤ 0.2) before any code is written. Nine Minds agents (socratic-interviewer, ontologist, seed-architect, evaluator, contrarian, hacker, simplifier, researcher, architect) execute the Double Diamond. Ralph mode loops with state persistence until verification passes — the boulder never stops. Use when user says "ralph", "ooo", "ooo interview", "ooo seed", "ooo run", "ooo evaluate", "ooo evolve", "ooo unstuck", "ooo status", "ooo ralph", "stop prompting", "start specifying", "specification first", "socratic interview", "don't stop", "must complete", "keep going", or "the boulder never stops".
Methodology for effective AI-assisted software development. Use when helping users build software with AI coding assistants, debugging AI-generated code, planning features for AI implementation, managing version control in AI workflows, or when users mention "vibe coding," Cursor, Windsurf, or similar AI coding tools. Provides strategies for planning, testing, debugging, and iterating on code written with LLM assistance.
Use when syncing skills from local folders, GitHub URLs, or skillsmp.com pages to multiple AI coding tool directories
Audit and optimise context window usage for AI coding tools (Claude Code, OpenCode, etc.). Estimates token breakdown, identifies waste (duplicate skills, overlapping rules, bloated instruction files, dirty git status, MCP server overhead), and provides actionable recommendations with projected savings. Use when the user says "context checkup", "reduce context", "check context", "context audit", "how big is my context", or when sessions feel sluggish.
Discover and install skills from multiple marketplaces for AI coding agents
Cross-tool compatibility workflow. Use when generating AGENTS.md files for compatibility with other AI coding tools, or creating tool-specific instruction files from CLAUDE.md.
Analyze and clean up duplicate skills across vibe coding tools. Use when user asks to analyze skills, find duplicates, or clean up their skill collection.
Operate OpenAI Codex CLI (terminal coding agent) to accomplish software engineering tasks. Use when the user asks to: run codex commands, use codex for coding tasks, execute codex exec for automation, do code review with codex, manage codex sessions (resume/fork), configure codex (config.toml, approval modes, sandbox), use codex cloud, set up MCP servers in codex, or any task involving the `codex` command-line tool. Triggers: codex, codex exec, codex review, codex cloud, codex mcp, codex resume, codex sandbox, openai codex.