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Found 42 Skills
Scaffold the Mimas agent instruction file tree for any repository — AGENTS.md at root, subdomain CONTEXT.md files, and the full agents-docs/ hierarchy (a sibling of any existing docs/, kept separate so human-maintained project docs stay untouched). Every file is tailored to the repo's actual tech stack, git platform, and conventions. Use this skill whenever someone wants to set up agent instructions, onboard a repo for AI-assisted development, add AGENTS.md / CONTEXT.md files, create engineering docs for agents, or mentions "set up agentic repository" or "mimas template". Even if they just say "set up this repo for agents" or "add agent docs", this is the skill to use.
Multi-Model Collaboration — Invoke gemini-agent and codex-agent for auxiliary analysis **Trigger Scenarios** (Proactive Use): - In-depth code analysis: algorithm understanding, performance bottleneck identification, architecture sorting - Large-scale exploration: 5+ files, module dependency tracking, call chain tracing - Complex reasoning: solution evaluation, logic verification, concurrent security analysis - Multi-perspective decision-making: requiring analysis from different angles before comprehensive judgment **Non-Trigger Scenarios**: - Simple modifications (clear changes in 1-2 files) - File searching (use Explore or Glob/Grep) - Read/write operations on known paths **Core Principle**: You are the decision-maker and executor, while external models are consultants.
Spec-Driven Development (SDD) methodology based on GitHub's SpecKit. Use for structured AI-assisted development with constitutional governance, phased workflows, and multi-agent coordination. Implements 7-phase process from constitution to implementation.
Modular Code Organization
Navigate the SLDD (Spec Loops Driven Development) process and choose the correct skill for the current stage. Use when starting a new feature or when unsure which step comes next.
Delegate coding tasks to Codex, Claude Code, or Pi agents via background process. Use when: (1) building/creating new features or apps, (2) reviewing PRs (spawn in temp dir), (3) refactoring large codebases, (4) iterative coding that needs file exploration. NOT for: simple one-liner fixes (just edit), reading code (use read tool), thread-bound ACP harness requests in chat (for example spawn/run Codex or Claude Code in a Discord thread; use sessions_spawn with runtime:"acp"), or any work in ~/clawd workspace (never spawn agents here). Claude Code: use --print --permission-mode bypassPermissions (no PTY). Codex/Pi/OpenCode: pty:true required.
Agent harness architecture — structure a project's agent context across layers for effective AI-assisted development. Covers CLAUDE.md, skills, design docs, hooks, and all artifacts that shape how an agent understands and operates in a codebase. Use when setting up or improving a project's agent configuration, when agent context feels bloated or disorganized, when onboarding a new project for AI-assisted development, or when the agent keeps losing architectural awareness mid-task. Trigger on phrases like "set up claude", "improve CLAUDE.md", "agent keeps forgetting", "context is too long", "harness setup", "organize agent context", "how should I structure my prompts". Supports arguments: `/harness audit` to evaluate an existing project's context architecture, `/harness init` to set up harness from scratch.
Keep AI tooling files (.claude, .codex, .cursor, .windsurf, .augment, .kiro, .cline, .roo, .gemini, etc.) on dev branch but exclude them from main/master. Use when managing branches, creating PRs to main, merging to main, or setting up a repo's branch strategy for AI-assisted development. Triggers on git merge/PR operations targeting main or master.
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.
Comprehensive guide for AI-assisted vibe coding. Use when the user wants to build applications through natural language prompts using tools like Lovable, Cursor, Replit, or Bolt. Includes best practices, pitfall awareness, tool-specific guidance, architectural decision support, and MVP scope definition with a bias toward cutting features aggressively to ship faster.
Enter copilot mode — human drives, Claude assists. Relaxes worktree enforcement, allows main commits.
Used when you need to perform Discover (reverse engineering) on legacy projects with existing code, consolidate repository facts into `.aisdlc/project/`, and you find that AI or teams frequently guess entry points and boundaries, have duplicate writing of indexes and details, or lack evidence chains leading to repeated rework.