Intelligence Route
Route tasks via the 3-tier model selector and learned patterns; emits a routing rationale via hooks_explain
- Skill ID
- ruvnet/ruflo/intelligence-route
- Publisher
- ruvnet
- Repository
- ruflo
- Installs
- 0
- Files
- 1
- Synced
- Sep 23, 2026
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
ruvnet/ruflo/intelligence-routeInstalls these files- SKILL.md
What this skill tells the agent
Intelligence Routing
Pick the optimal agent + model tier for a task using learned patterns + the 3-tier router. Emits a hooks_explain rationale so the choice is auditable.
When to use
Before starting any non-trivial task. Replaces manual agent selection with data-driven decisions.
Steps
- Get an agent recommendation —
mcp__plugin_ruflo-core_ruflo__hooks_routewith the task description. Returns{ recommended, confidence, reasoning }. - Get a model tier recommendation —
mcp__plugin_ruflo-core_ruflo__hooks_model-routefor Haiku/Sonnet/Opus selection. - Search for similar past patterns —
mcp__plugin_ruflo-core_ruflo__hooks_intelligence_pattern-searchto find prior successes. - Predict outcome —
mcp__plugin_ruflo-core_ruflo__neural_predictwith the task description for a confidence-scored prediction. - Spawn the recommended agent at the recommended model tier.
- (If `--why` was passed) — call
mcp__plugin_ruflo-core_ruflo__hooks_explainto surface the routing rationale to the user. - After task completes — call
mcp__plugin_ruflo-core_ruflo__hooks_model-outcomewithsuccess: true|falseto train the router.
3-Tier Model Routing
| Tier | Handler | Latency | Cost | When |
|---|---|---|---|---|
| 1 | Deterministic codemod (TS compiler) | ~1ms | $0 | Structural transforms with no LLM: var-to-const, remove-console, add-logging |
| 2 | Haiku | ~500ms | ~$0.0002 | Low complexity (<30%), bug fixes, quick patches |
| 3 | Sonnet/Opus | 2–5s | $0.003–$0.015 | Complex reasoning, architecture, security, multi-file refactors |
When hooks_route returns [CODEMOD_AVAILABLE] for a deterministic intent (var-to-const, remove-console, add-logging), call mcp__plugin_ruflo-core_ruflo__hooks_codemod with the intent + file — it applies the transform via the TypeScript compiler at $0, no LLM. Note: add-types, add-error-handling, async-await require judgement and route to a model (Tier 2/3) per ADR-143; they are NOT $0 codemods. Agent Booster is a fast-apply merge engine for LLM-produced edits, not the Tier-1 path.
Recording outcomes
Closing the routing loop is mandatory:
# Success
mcp tool call hooks_model-outcome --json -- '{"taskId": "T123", "success": true, "model": "haiku"}'
# Failure with reason
mcp tool call hooks_model-outcome --json -- '{"taskId": "T123", "success": false, "model": "haiku", "reason": "complexity-misjudged"}'The router learns from these calls. Skipping them = no learning.
CLI alternative
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"More from ruvnet
Use this skill in a project
Open any RiverX project, search the Skills panel for ruvnet/ruflo/intelligence-route, and install it in one click.
