ruvnet/ruflo1 file

Intelligence Route

Route tasks via the 3-tier model selector and learned patterns; emits a routing rationale via hooks_explain

Specification
Skill ID
ruvnet/ruflo/intelligence-route
Publisher
ruvnet
Repository
ruflo
Installs
0
Files
1
Synced
Sep 23, 2026
How to use it

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

  1. Get an agent recommendation — mcp__plugin_ruflo-core_ruflo__hooks_route with the task description. Returns { recommended, confidence, reasoning }.
  2. Get a model tier recommendation — mcp__plugin_ruflo-core_ruflo__hooks_model-route for Haiku/Sonnet/Opus selection.
  3. Search for similar past patterns — mcp__plugin_ruflo-core_ruflo__hooks_intelligence_pattern-search to find prior successes.
  4. Predict outcome — mcp__plugin_ruflo-core_ruflo__neural_predict with the task description for a confidence-scored prediction.
  5. Spawn the recommended agent at the recommended model tier.
  6. (If `--why` was passed) — call mcp__plugin_ruflo-core_ruflo__hooks_explain to surface the routing rationale to the user.
  7. After task completes — call mcp__plugin_ruflo-core_ruflo__hooks_model-outcome with success: true|false to train the router.

3-Tier Model Routing

TierHandlerLatencyCostWhen
1Deterministic codemod (TS compiler)~1ms$0Structural transforms with no LLM: var-to-const, remove-console, add-logging
2Haiku~500ms~$0.0002Low complexity (<30%), bug fixes, quick patches
3Sonnet/Opus2–5s$0.003–$0.015Complex 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"

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.

Use this skill