Skill Factory#

Turn recurring pain points into published skills. Automatically.

Why This Exists#

Building skills manually takes 30 minutes: write SKILL.md, write the script, test, package, publish. The factory cuts this to 10 minutes by structuring the workflow and automating the boring parts.

More importantly: it connects to your .learnings/ error log. When a problem recurs 3+ times, the factory flags it as a skill candidate. Your mistakes become products.

Prerequisites#

• .learnings/ERRORS.md and/or .learnings/LEARNINGS.md in your workspace (see self-improving-agent skill or create manually)
• ClawHub CLI authenticated ( npx clawhub@latest login)
• Python 3 (for packaging via skill-creator)

Commands#

Scan for skill candidates#

bash

node scripts/factory.js scan

Reads .learnings/ and finds entries with 3+ recurrences and a known fix. These are ready for extraction into skills.

Build from a pain point description#

bash

node scripts/factory.js build "agents keep double-replying to the same post"

Creates a skill scaffold at skills/public/<slug>/ with a .factory-prompt.md describing what to build. Then you (the LLM) write the SKILL.md and script.

Build from a .learnings/ entry#

bash

node scripts/factory.js from-error ERR-20260316-001

Same as build, but pulls the description and fix from an existing error entry.

Publish#

bash

node scripts/factory.js publish skills/public/my-skill

Packages and publishes to ClawHub in one step. Cleans up factory files first.

The Pipeline#

text

Mistake → .learnings/ERRORS.md → scan (3+ recurrences) → from-error → write skill → publish

Learnings Format#

The factory expects entries in this format:

markdown

## [ERR-20260316-001] Short description
**Recurrences:** 3 | **Last:** 2026-03-16
**What failed:** what went wrong
**Fix:** what actually solved it

Or for learnings:

markdown

## [LRN-20260316-001] Short description
**Category:** best_practice
**Recurrences:** 3 | **Last:** 2026-03-16
**What happened:** context
**The lesson:** what's correct

Integrating With Heartbeats#

Add to your heartbeat config to surface new candidates:

yaml

collectors:
  - name: skill-candidates
    command: "node tools/skill-factory/factory.js scan --count"
    format: text
    alert: "> 0"
    summary: "{{output}} skill candidates ready for extraction"

CLI Reference#

text

node scripts/factory.js <command>

  scan                    Find extractable patterns in .learnings/
  scan --count            Just print the count (for heartbeat integration)
  build "description"     Scaffold a skill from a pain point
  from-error <id>         Scaffold from a .learnings/ entry
  publish <dir>           Package + publish to ClawHub