famou-artifact-generator

name	famou-artifact-generator
description	Interactive end-to-end Famou workflow for defining, implementing, and solving optimization tasks. The workflow typically proceeds in three stages: (1) understand the data and define the task, producing `problem.md`; (2) implement and validate `evaluator.py`, `init.py`, and `prompt.md` from the task definition; (3) run deep solving through Famou. Trigger this skill whenever the user wants to define, clarify, create, or fix a Famou task; prepare Famou experiment artifacts; write or update `problem.md`, `evaluator.py`, `init.py`, or `prompt.md`; run Famou; do deep solving; or solve an optimization, ML, or search problem with evolutionary methods. Even if the user simply says "help me make a Famou task", "help me solve this", or "run Famou", trigger this skill whenever the surrounding context indicates an optimization or search task. Also trigger when the user describes a combinatorial optimization, scheduling, routing, or ML problem without mentioning Famou — treat it as a potential Famou task.
metadata	{"author":"famou-group","version":"9.0"}

FaMou Workflow Router

Route user tasks to the correct workflow.

Responsibilities

1. Identify task type from user description
2. Select exactly one workflow file in references/
3. Delegate execution to that workflow
4. Do not embed step details — those belong in workflows and components

Routing Rules

Priority order:

1. User choice: If the user explicitly names a workflow, use it
2. Automatic routing: Otherwise, match by task characteristics:

Workflow Selection

Workflow	When to Use
general	Generic optimization, search, planning, scheduling, or ML tasks — all other cases

Execution Flow

1. Route: Determine workflow based on routing rules
2. Delegate: Read the selected file in references/ and follow its instructions
3. Exit: After delegation, router's job is complete

If uncertain, default to general workflow and note assumptions.