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A5c AI/Swarm Orchestration — measured AI agent skill | DecimalAI

a5c-ai/swarm-orchestration

SkillScore50Maintained

Multi-agent swarm formation and coordinated execution with topology-aware agent deployment, consensus protocols, and anti-drift enforcement.

by a5c-ai

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

AI Engineer pack

decimalai skills pull a5c-ai-swarm-orchestration

Get this skill — curl · raw file

curl -fsSL https://app.decimal.ai/s/a5c-ai-swarm-orchestration/SKILL.md

Raw file: /s/a5c-ai-swarm-orchestration/SKILL.md ↗ · machine-readable summary at /s/a5c-ai-swarm-orchestration.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

22 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 9d ago

—-28% tokens0% turns50% of whole cases pass with skill (11/22)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-03	✗→✓	▲ Improved	-13%	0%
case-07	✗→✓	▲ Improved	-38%	0%
case-08	✗→✓	▲ Improved	-48%	0%
case-09	✗→✓	▲ Improved	-19%	0%
case-10	✗→✓	▲ Improved	-65%	0%

Showing 5 of 22 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 7/31/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

a5c-ai / babysitter

library/methodologies/ruflo/skills/swarm-orchestration/SKILL.md

View on GitHub ↗

License MITImported 7/31/2026Version v1

Skill contents

SKILL.md

Tasks needing coordinated parallel execution
When consensus among agents is required for quality
Projects requiring anti-drift enforcement during execution

Process

Topology Selection - Analyze task and agent pool to select optimal topology
Agent Assignment - Assign Queen (Strategic/Tactical/Adaptive) and Worker roles
Consensus Init - Initialize Raft/Byzantine/Gossip/CRDT protocol
Parallel Execution - Distribute subtasks with shared memory
Anti-Drift Checkpoints - Validate alignment every N subtasks
Consensus Voting - Weighted voting (Queen=3x) for final decision

Topologies

Mesh: All-to-all communication, best for small swarms (<8 agents)
Hierarchical: Queen coordinates workers, best for large/structured tasks
Ring: Sequential handoff, best for pipeline/transformation tasks
Star: Central coordinator fan-out, best for independent subtasks

Agents Used

agents/strategic-queen/ - Long-term planning swarms
agents/tactical-queen/ - Execution coordination swarms
agents/adaptive-queen/ - Real-time optimization swarms
agents/swarm-coordinator/ - Topology management

Tool Use

Invoke via babysitter process: methodologies/ruflo/ruflo-swarm-coordination

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Other measured skills in the registry, with their headline benchmark lift.