intelligence-route

Original：🇺🇸 English

Translated

Route tasks to optimal agents using learned patterns, model recommendations, and confidence scoring

6installs

Sourceruvnet/ruflo

Added on2026-05-03

NPX Install

npx skill4agent add ruvnet/ruflo intelligence-route

SKILL.md Content

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Intelligence Routing

Route tasks to the best agent and model based on learned patterns.

When to use

Before starting any task, use intelligence routing to get the optimal agent type, model tier, and confidence score. This replaces manual agent selection with data-driven decisions.

Steps

Get routing recommendation — call
```
mcp__claude-flow__hooks_route
```
with the task description
Check model recommendation — call
```
mcp__claude-flow__hooks_model-route
```
for the optimal model tier (Haiku/Sonnet/Opus)
Search for similar patterns — call
```
mcp__claude-flow__hooks_intelligence_pattern-search
```
to find past successes
Predict outcome — call
```
mcp__claude-flow__neural_predict
```
with the task description
Spawn the recommended agent at the recommended model tier
Record outcome — after task completes, call
```
mcp__claude-flow__hooks_model-outcome
```
to train the router

3-Tier Model Routing

Tier	Handler	When
1	Agent Booster (WASM)	Simple transforms — skip LLM entirely
2	Haiku	Low complexity tasks (<30%)
3	Sonnet/Opus	Complex reasoning, architecture, security

CLI alternative

bash

npx @claude-flow/cli@latest hooks route --task "description"
npx @claude-flow/cli@latest hooks pre-task --description "description"
npx @claude-flow/cli@latest hooks explain --topic "routing decision"

Viewing intelligence stats

Call

mcp__claude-flow__hooks_intelligence_stats

or: