Agent skill for mesh-coordinator - invoke with $agent-mesh-coordinator
40
Quality
7%
Does it follow best practices?
Impact
99%
2.60xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agents/skills/agent-mesh-coordinator/SKILL.mdMesh initialization and lifecycle workflow
swarm_init maxAgents
0%
100%
swarm_init strategy
100%
100%
network_init message type
0%
100%
Gossip consensus protocol
0%
100%
Consensus threshold
0%
100%
Memory namespace
0%
100%
Monitor interval
0%
100%
Monitor metrics
0%
100%
Shutdown message
0%
100%
Performance report params
50%
100%
Without context: $0.7470 · 3m 7s · 30 turns · 408 in / 10,750 out tokens
With context: $0.3699 · 1m 12s · 18 turns · 270 in / 4,088 out tokens
Fault detection and partition recovery
Heartbeat timeout
0%
100%
Heartbeat interval
0%
100%
Read-only on partition
100%
100%
Majority quorum to continue
100%
100%
heartbeat_monitor strategy
0%
100%
failover_recovery strategy
0%
100%
DHT replication factor
0%
100%
topology_optimize call
0%
100%
33% BFT threshold
0%
80%
Without context: $0.3181 · 1m 49s · 11 turns · 16 in / 6,968 out tokens
With context: $1.0942 · 4m 21s · 30 turns · 37 in / 17,693 out tokens
Task distribution strategies
Work stealing: pull when idle
100%
100%
Work stealing: push when overloaded
100%
100%
Overloaded threshold
100%
100%
Underutilized threshold
0%
100%
Auction: capability_match weight
100%
100%
Auction: current_load weight
100%
100%
Auction: past_performance weight
100%
100%
Auction: resource_availability weight
100%
100%
Capability routing threshold
0%
100%
Without context: $0.3636 · 1m 54s · 16 turns · 19 in / 7,453 out tokens
With context: $0.5038 · 2m 6s · 19 turns · 273 in / 7,440 out tokens
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Table of Contents
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.