agent-room
Agent Room
Meta — Stochastic Multi-Agent Discussion. View a problem through multiple expert perspectives via debate or polling.
Core Question: "What do multiple perspectives converge on — and where do they genuinely disagree?"
This is the centralized multi-perspective analysis capability. When any skill needs debate, consensus, or multiple viewpoints on a decision, it invokes agent-room. Structured decomposition work (like task-breakdown) may retain specialized agents for their domain.
Two Entry Points
1. Standalone (user invokes directly)
User runs /agent-room "Should we use a monorepo or polyrepo?" — the skill runs a full debate or poll session.
2. Sub-routine (another skill invokes mid-flow)
The discover skill hits a complex decision during conversation. It invokes agent-room with the specific decision framed, waits for the result, then continues the conversation.
Sub-routine protocol (for invoking skills):
More from hungv47/meta-skills
task-breakdown
Decomposes a spec or architecture into buildable tasks with acceptance criteria, dependencies, and implementation order for AI agents or engineers. Produces `skills-resources/meta/tasks.md`. Not for clarifying unclear requirements (use discover) or designing architecture (use system-architecture). For code quality checks after building, see fresh-eyes.
80discover
Conversational discovery — adapts from quick scoping (3-5 questions) to deep interviews (multi-round). Talk until we're clear, then build. Produces inline decisions; optionally saves spec.md or scope contract. Not for multi-perspective debate (use agents-panel). Not for decomposing work (use task-breakdown). Not for diagnosing a known metric decline or root-causing a problem (use diagnose).
77review-chain
Post-implementation quality check via fresh-eyes review. Chain: Implement → Review (independent agent) → Resolve (if issues). Max 2 rounds. Auto-triggers for security-sensitive and data-mutation code. Not for code refactoring (use code-cleanup). Not for decision analysis (use agent-room).
61navigate
Artifact status + multi-phase orchestration. Scan what exists, check freshness, compose and track complex workflows across sessions. Not for skill routing (the agent does that proactively).
57fresh-eyes
Post-implementation quality check via fresh-eyes review. Chain: Implement → Review (independent agent) → Resolve (if issues). Max 2 rounds. Auto-triggers for security-sensitive and data-mutation code. Not for code refactoring (use code-cleanup). Not for decision analysis (use agents-panel).
17agents-panel
Multi-agent discussion rooms — debate or poll a problem from multiple perspectives. Standalone or invoked by other skills as a sub-routine. Mode=debate: N agents argue in rounds, converge. Mode=poll: N agents independently analyze, aggregate by consensus. Not for implementation (use system-architecture). Not for verification (use fresh-eyes). For clarifying requirements first, see discover. For decomposing work after a decision, see task-breakdown.
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