compose

name	compose
description	Compose method atoms into a training recipe. Use when user says "组合recipe", "compose recipe", "build training config", or wants to create a new experiment configuration.
argument-hint	["atom-names or description"]
allowed-tools	Bash(*), Read, Write, Grep, Glob

Compose — Training Recipe Builder

Compose a training recipe from: $ARGUMENTS

Pipeline

1. Load — Read method atoms from recipes/registry/method_atoms.json
2. Select — Pick atoms matching the user's request (by name or description)
3. Combine — Merge selected atoms into a coherent Recipe IR:
   • Resolve conflicts (e.g., two different reward functions → composite)
   • Set model, dataset mix, trainer type, and backend
   • Configure evaluation benchmarks and seeds
   • Set budget constraints
4. Validate — Validate the composed recipe against recipes/schema/recipe.schema.json
5. Save — Write recipe to recipes/examples/<name>.recipe.json

Constraints

• Every recipe MUST specify: id, name, model, dataset, trainer
• Default RL backend is veRL; default SFT backend is TRL
• Include at least one ablation study in every recipe
• Set reasonable budget defaults (24h for SFT, 48h for RL on A100)
• Seeds default to [42, 123, 456]