Choose an agent and model tier using the task description and learned patterns. The skill can explain its recommendation, use compiler-based edits for supported simple changes, and record task outcomes to inform future routing decisions.
Route tasks via the 3-tier model selector and learned patterns; emits a routing rationale via hooks_explain
Review the instructions the agent will receive before you install.
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.
Before starting any non-trivial task. Replaces manual agent selection with data-driven decisions.
mcp__plugin_ruflo-core_ruflo__hooks_route with the task description. Returns { recommended, confidence, reasoning }.mcp__plugin_ruflo-core_ruflo__hooks_model-route for Haiku/Sonnet/Opus selection.mcp__plugin_ruflo-core_ruflo__hooks_intelligence_pattern-search to find prior successes.mcp__plugin_ruflo-core_ruflo__neural_predict with the task description for a confidence-scored prediction.--why was passed) — call mcp__plugin_ruflo-core_ruflo__hooks_explain to surface the routing rationale to the user.mcp__plugin_ruflo-core_ruflo__hooks_model-outcome with { task, model, outcome: "success"|"failure"|"escalated" } to train the router.| 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.
Closing the routing loop is mandatory:
# Success (task, model and outcome are all required; model is haiku|sonnet|opus)
npx @claude-flow/cli@latest mcp exec -t hooks_model-outcome -p '{"task": "fix the flaky retry test", "model": "haiku", "outcome": "success"}'
# The model was too small and the work moved up a tier: use "escalated"; use "failure" if it did not work out
npx @claude-flow/cli@latest mcp exec -t hooks_model-outcome -p '{"task": "fix the flaky retry test", "model": "haiku", "outcome": "escalated"}'
The router learns from these calls. Skipping them = no learning.
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 --task "description" --verbose
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Compare models available through the HuggingFace router with chat-ui configuration, research missing models, and write short English descriptions of their architecture and capabilities. Add entries to both production and development configuration files and commit the changes.
Create an Architecture Decision Record, a document for recording important design choices, with the next sequential number. It generates a Markdown template, registers the record in AgentDB, and links related decisions found through search.
Build a searchable index and relationship graph from ADRs, records of architectural decisions. Import two supported document formats, refresh existing metadata without duplicate relationships, and review summaries of statuses, missing references, and inconsistencies.
Rebuild the index of ADRs, records of architectural decisions, after files or relationship lines are deleted. It clears stored records and relationships, indexes the files still present, and checks that the final record count matches.
Review code changes against accepted Architecture Decision Records, documents that capture agreed design choices. Report violations, outdated references, compliant changes, and areas without ADR coverage, then suggest code fixes or a new decision record where appropriate.
Check saved architecture decision records (ADRs) for broken references, circular replacement relationships, and inconsistent statuses. Use the results to verify imported records or stop a CI check when selected integrity rules fail.