---
name: training-harvester
description: >
  Harvest training data from Claude Code, Codex, and Wall-E sessions.
  Extracts prompt/response pairs, correlates with git outcomes, and writes
  JSONL files for model fine-tuning. Runs daily at 3 AM.
version: 1.0.0
author: wall-e
execution: script
entry: run.js
trigger:
  type: interval
  schedule: "daily at 3am"
tags: [training, harvesting, fine-tuning, data]
permissions:
  - brain:read
  - brain:write
  - filesystem:read
---
# Training Data Harvester

## What This Skill Does

Harvests training data from all available sources:

1. **Claude Code sessions** — parses JSONL conversation logs from `~/.claude/projects/`
2. **Codex sessions** — parses JSONL from `~/.codex/sessions/`
3. **Wall-E chat** — extracts user/assistant pairs from the brain DB
4. **Wall-E tasks** — extracts completed task descriptions and results

For coding sessions, correlates with git commits to determine outcome quality
(committed = high quality, reverted = low quality).

## Output

- JSONL files written to `~/.walle/data/training/harvested/YYYY-MM-DD.jsonl`
- Each line is a training sample with: prompt, response, task_type, quality_label
- Incremental by default — only processes new data since last run
- Deduplicates by content hash

## Schedule

Runs daily at 3 AM. Can also be triggered manually.
