489 tagged agent-framework, measured the same way as everything else here.
Browse within: agent-orchestration 107ai-orchestration 61AI Platform 60ai-automation 60enterprise-ai 60ai-coding-agent 40bash 40agentic-development 30agents-md 30ai-governance 30ai-guardrails 30agentic-workflow 28Multi-Agent 25ai-assistant 23
Command Claude Code
Command "wish" from namastexlabs/automagik-hive, covering /wish - automagik forge wish creation system, 🎯 wish creation workflow, phase 0: branch creation & setup, determine branch name from user request and create and switch to wish branch.
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Use to initialize RDF governance on a new or existing repository.
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Use when a spec is ready and you need an execution-grade, phase-by-phase implementation plan a fresh engineer can run mechanically.
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Use when starting a new feature, subsystem, or design change: turns an idea into an architecture-grade spec through research-driven dialogue.
Command Claude Code
Implement tasks from an OpenSpec change (Experimental).
Command Claude Code
Archive a completed change in the experimental workflow.
Command Claude Code
Enter explore mode - think through ideas, investigate problems, clarify requirements.
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Command dispatcher for brainstorm.
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Command dispatcher for discover.
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Command dispatcher for propose.
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Handle character work for this production — designing a new one, reviewing what exists, or revising a character already in use. Figure out which of these I mean from what follows, and if it's genuinely ambiguous, ask.
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Re-run the quality checks on the current cut.
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Show me the plan before you build it.
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Fix build and type failures with minimal diffs.
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Drive a feature from plan to implementation to review.
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Coordinate issue intake, branch work, and merge steps.
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Execute a learned Maestro flow ("action") by name with optional -e KEY=VALUE parameters. Looks the flow up via packages/rn-dev-agent-core/dist/learned-actions.js (same inventory as /rn-dev-agent:list-learned-actions), then replays it via cdprunaction — auto-repair-aware orchestration with structured RunRecords (GH.
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Send feedback or report a bug for the rn-dev-agent plugin. Collects sanitized environment context and creates a GitHub issue. No sensitive data (paths, secrets, PII) is transmitted.
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Full onboarding for a new project — runs /doctor diagnostics, then injects the CLAUDE.md template + nav-ref instrumentation + Zustand store exposure so the plugin works without the user having to read documentation.
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Full PR review pipeline (local agents + external feedback + triage + fixes).
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Full codebase audit: launches 159 specialized agents to find issues across Python/React/Go/docs/website, writes findings to audit/latest/findings/, then triages with user.
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Pre-PR review pipeline (checks + review agents + fixes + create PR).
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Deploy the application to production.
MN-Lizard-Team/aiyu-multi-agent
Command Cursor
You MUST start your FIRST response with this exact agent activation line.