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fan-out

Parallel agent orchestration for OST exploration. Fan-out multiple solution explorations, fan-in results to compare and select winners.

35estrelas
Atualizado há 4 meses

Ver no GitHub ↗ Licença: MIT

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/plugin marketplace add haabe/mycelium

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Fan-Out / Fan-In Orchestration

When to Use

  • OST has 2+ solutions for the same opportunity that need parallel exploration
  • Independent delivery work items that can be parallelized
  • Multiple research streams needed simultaneously

Workflow

1. Prepare (Lead Agent)

  • Read .claude/canvas/opportunities.yml
  • Identify solutions needing parallel work
  • For each: identify riskiest assumption and design test

2. Fan-Out (Spawn Workers)

For each solution:

  • Spawn subagent or Agent Team member
  • Provide: clear task, read-only canvas context, worktree isolation, time bound
  • Each worker runs independently

3. Fan-In (Collect Results)

  • Collect all worker results
  • Update ICE scores in canvas
  • Run /mycelium:bias-check on combined findings
  • Select winner(s) based on evidence
  • Log decision in .claude/harness/decision-log.md

Leaf Bakeoff Mode

When comparing competing OST leaves for the same opportunity:

  • Each worker returns a structured scorecard (Four Risks + ICE + assumption test result + segment fit)
  • Lead agent applies winner selection rules: clear winner (>20% ICE delta), close race (tiebreaker), segment split (both advance), both fail (archive and re-evaluate)
  • Losers are archived to .claude/canvas/archived-solutions.yml with full evidence snapshot

See ${CLAUDE_PLUGIN_ROOT}/orchestration/leaf-bakeoff.md for the complete bakeoff protocol.

Rules

  • Workers NEVER write to canvas (lead agent does)
  • Workers NEVER progress diamonds
  • Lead agent ALWAYS runs bias check on combined results
  • Minimum 2 workers for meaningful comparison
  • Maximum 3 leaves per bakeoff (respects L3 WIP ceiling)

See ${CLAUDE_PLUGIN_ROOT}/orchestration/agent-teams.md for full orchestration patterns.

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