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Add swarm-orchestrator skill#889

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michaelwinczuk wants to merge 1 commit intoanthropics:mainfrom
michaelwinczuk:add-swarm-orchestrator
Open

Add swarm-orchestrator skill#889
michaelwinczuk wants to merge 1 commit intoanthropics:mainfrom
michaelwinczuk:add-swarm-orchestrator

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Summary

Adds a swarm-orchestrator skill that teaches Claude to design, build, and debug multi-agent systems.

  • 8 agent archetypes — Perceiver, Classifier, Analyzer, Synthesizer, Validator, Resolver, Planner, Executor — with design rules and deterministic-first guidance
  • 5 communication patterns — Sequential Chalkboard, Fan-Out/Fan-In, Pipeline with Gates, Adversarial Pair, Iterative Refinement
  • Deterministic-first cascade — Try rules → local model → API → frontier. Typical 50-82% deterministic solve rate
  • Chalkboard protocol — Shared immutable state for agent communication and debugging
  • Cost optimization — Per-agent and per-pipeline budgets, deterministic ratio tracking
  • Debugging methodology — Chalkboard trace analysis, common failure patterns, health metrics

Included Files

  • SKILL.md — Core skill instructions (~300 lines)
  • scripts/validate_pipeline.py — Pipeline definition validator (cycles, schemas, budgets)
  • scripts/simulate.py — Chalkboard simulation engine for dry runs
  • references/archetypes.md — Detailed archetype guide with decision matrix
  • references/examples.md — 4 complete swarm designs + debugging walkthrough
  • evals/evals.json — 5 test cases

Why This Skill

Anthropic shipped agent teams in Opus 4.6. 123+ plugins in the marketplace. Zero teach multi-agent orchestration. This fills the biggest architectural gap — how to design agent systems that are debuggable, cost-efficient, and deterministic-first.

Companion to knowledge-graph-reasoning (#888) — structured knowledge + agent orchestration = complete autonomous systems.

Test plan

Built by Swarm Labs USA | Standalone repo

🤖 Generated with Claude Code

Skill for designing, building, and debugging multi-agent systems.

Features:
- 8 agent archetypes (Perceiver, Classifier, Analyzer, Synthesizer, Validator, Resolver, Planner, Executor)
- 5 communication patterns (Sequential Chalkboard, Fan-Out, Pipeline with Gates, Adversarial Pair, Iterative Refinement)
- Deterministic-first cascade for cost optimization
- Chalkboard protocol for shared agent state
- Pipeline validation script (cycles, schemas, budgets)
- Chalkboard simulation engine
- 5 eval test cases

Production-tested across 5+ swarms with 50-82% deterministic solve rates.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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