task-router

Routes user queries to cognitive atom chains and records execution in pipeline_trace.json.

6|1|Updated May 11, 2026
One-click install
npx skills add https://github.com/yakeworld/Synthos --skill task-router-yakeworld
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: task-router
Source: https://github.com/yakeworld/Synthos/tree/main/skills/core/task-router
Command: npx skills add https://github.com/yakeworld/Synthos --skill task-router-yakeworld

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? In a multi-skill research system, deciding which skills to invoke, in what order, and under which execution mode is error-prone. This Skill acts as the system entry point: it analyzes each user query, classifies its complexity, selects an execution mode (standard chain, exploratory loop, research double-loop, or parallel), and dispatches work to the correct cognitive atoms while logging every decision. ## Core Features & Use Cases - Query-to-Mode Routing: Classifies queries into standard chain, exploratory loop, research double-loop, or parallel execution, then selects the matching atom chain (ACQ→EXT→ASC→HYP→ARG→VER) without skipping or over-invoking steps. - Sub-Agent Delegation Discipline: Enforces delegate_task rules—pass the user's original goal with an empty context, never micro-manage sub-agents, and split batches of more than 10 papers into parallel subtasks. - Traceable Execution: Creates outputs/{session_id}/pipeline_trace.json recording mode, chain, per-atom status, loop state, and gene activation metadata for reproducibility. - Use Case: A user asks to "search 3D nystagmus literature"; the router selects the standard chain (knowledge-acquisition → knowledge-extraction), creates the pipeline trace, and delegates the task verbatim to a sub-agent. ## Quick Start Ask the agent to route the query "search 3D nystagmus literature" and verify that pipeline_trace.json records a standard route with the knowledge-acquisition and knowledge-extraction atoms.

Frequently Asked Questions about task-router

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I route a user query to the right skill chain?

Analyze the query intent and map it to an execution mode: search or extract tasks use the standard chain (ACQ→EXT), optimization questions use the exploratory loop (HYP→ARG→VER), and full research tasks use the research double-loop across all atoms. Record the decision in pipeline_trace.json.

How should delegate_task be called for sub-agents?

Pass the user's original words as the goal and an empty string as context. Sub-agents have their own skill library and routing rules, so micro-management instructions in context cause interruptions; tested runs show trusted delegation succeeds where micro-managed versions fail.

When should a task use parallel execution mode?

Use parallel mode when the query contains independent subtasks, such as searching two research directions simultaneously, or when a batch exceeds ten papers. Each subtask runs its own atom chain independently and results are merged afterward.

What is pipeline_trace.json used for?

pipeline_trace.json is the routing evidence record created per session under outputs/{session_id}/. It stores the session ID, selected mode, atom chain, per-atom status, loop state, and gene activation metadata so every routing decision is auditable and reproducible.

What are the limitations of the task router?

The router performs no cognitive operations itself; it only classifies queries, orchestrates chains, and tracks loop state. Content judgments such as whether results support a hypothesis belong to the HYP and VER atoms, and one-shot queries should not use loop modes.