agent-resource-allocator
Agent skill for resource-allocator - invoke with $agent-resource-allocator
Install with Tessl CLI
npx tessl i github:ruvnet/claude-flow --skill agent-resource-allocator36
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillEvaluation — 80%
↑ 5.00xAgent success when using this skill
Validation for skill structure
Evaluation results
72%
50%Swarm Resource Optimizer
MCP resource allocation workflow
metrics_collect components
0%
100%
performance_report call
0%
100%
bottleneck_analyze call
0%
100%
daa_resource_alloc call
0%
100%
Correct call sequence
0%
100%
Concurrent collection
100%
100%
Gradual rollout
100%
0%
Result structure
0%
0%
agent_metrics call
0%
0%
Five allocator types
0%
100%
Without context: $0.2747 · 1m 16s · 14 turns · 21 in / 4,854 out tokens
With context: $0.4538 · 1m 33s · 19 turns · 273 in / 5,634 out tokens
68%
64%Adaptive Swarm Scaling Engine
ML predictive scaling
LSTM model present
0%
100%
RandomForest model present
0%
100%
IsolationForest model present
0%
100%
Ensemble predictor present
25%
100%
0.85 accuracy gate
0%
100%
Ready false on low accuracy
0%
100%
DQN learningRate
0%
100%
DQN epsilonDecay
25%
100%
DQN memorySize
0%
0%
Genetic algorithm parameters
0%
0%
Pareto front selection
0%
0%
mcp.swarm_scale call
0%
0%
Without context: $0.5693 · 2m 23s · 26 turns · 33 in / 9,420 out tokens
With context: $0.8478 · 3m 30s · 24 turns · 435 in / 14,426 out tokens
100%
76%Resilient Swarm Infrastructure Framework
Circuit breaker and fault tolerance
Three circuit states
100%
100%
Default thresholds
0%
100%
Six circuit metrics
20%
100%
Adaptive threshold adjustment
62%
100%
Threshold minimums enforced
0%
100%
Bulkhead six components
30%
100%
KPI efficiency category
0%
100%
KPI performance category
0%
100%
KPI reliability category
0%
100%
npx claude-flow metrics-collect
33%
100%
npx claude-flow swarm-scale
33%
100%
npx claude-flow bottleneck-analyze
33%
100%
mcp.topology_optimize after scale
0%
100%
Without context: $0.5226 · 2m 47s · 15 turns · 22 in / 11,922 out tokens
With context: $0.6998 · 2m 40s · 25 turns · 29 in / 10,322 out tokens
- Evaluated
- Agent
- Claude Code
- Model
- Unknown
Table of Contents
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