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agent-adaptive-coordinator

Agent skill for adaptive-coordinator - invoke with $agent-adaptive-coordinator

47

1.51x

Quality

17%

Does it follow best practices?

Impact

100%

1.51x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.agents/skills/agent-adaptive-coordinator/SKILL.md
SKILL.md
Quality
Evals
Security

Evaluation results

100%

37%

Distributed Task Router: Topology Recommendation Engine

Topology selection decision logic

Criteria
Without context
With context

Hierarchical threshold: complexity

0%

100%

Hierarchical threshold: coordination

0%

100%

Mesh threshold: parallelizability

20%

100%

Mesh threshold: fault tolerance

12%

100%

Ring for sequential

77%

100%

Hybrid for mixed

88%

100%

All four topologies present

100%

100%

WorkloadAnalyzer class

100%

100%

Numeric score inputs

100%

100%

routing_decisions.json produced

100%

100%

Each topology demonstrated

100%

100%

No circular topology logic

83%

100%

Without context: $0.3489 · 1m 28s · 20 turns · 26 in / 5,265 out tokens

With context: $0.4843 · 1m 46s · 19 turns · 272 in / 6,503 out tokens

100%

39%

Smart Agent Pool Manager

Agent scoring and predictive scaling

Criteria
Without context
With context

Compatibility weight 0.6

0%

100%

Performance prediction weight 0.4

0%

100%

Capacity buffer 0.2

100%

100%

Scale-up threshold

50%

100%

Scale-down threshold

30%

100%

Target capacity formula

90%

100%

AgentAllocator class

100%

100%

learn_from_outcome method

100%

100%

PredictiveScaler class

100%

100%

allocation_log.json produced

100%

100%

Scores in allocation log

66%

100%

Without context: $0.4602 · 1m 59s · 20 turns · 26 in / 7,815 out tokens

With context: $0.5012 · 1m 40s · 24 turns · 320 in / 6,313 out tokens

100%

26%

Safe Coordinator Migration Framework

Topology transition protocol and rollback

Criteria
Without context
With context

Phase 1: Pre-Migration Analysis

100%

100%

Phase 2: Migration Planning

100%

100%

Phase 3: Gradual Transition

100%

100%

Phase 4: Post-Migration Optimization

100%

100%

Rollback threshold: performance degradation 25%

70%

100%

Rollback threshold: error rate 15%

0%

100%

Rollback threshold: agent failure 30%

0%

100%

Snapshot fields

100%

100%

Snapshot taken before transition

100%

100%

Rollback triggered in demo

100%

100%

migration_report.json produced

100%

100%

All three thresholds checked

50%

100%

Without context: $0.3882 · 1m 42s · 17 turns · 24 in / 7,010 out tokens

With context: $0.9772 · 3m 11s · 36 turns · 290 in / 12,630 out tokens

Repository
ruvnet/claude-flow
Evaluated
Agent
Claude Code
Model
Claude Sonnet 4.6

Table of Contents

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