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PantaniPantani/ableton-mind/.claude/skills/device-schema-extraction/SKILL.md

device-schema-extraction

Skill9 starsChanged 5 months agoMITView on GitHub

How to extract, complete and validate Ableton Live native device JSON schemas for the ableton-mind knowledge base.

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Use this skill when populating src/knowledge/devices, indexing packs or changing scripts/extract-device-schemas.mjs.

    line 8
  2. Distinctive:

    Default.adv parsing for saved default state.

    line 13
  3. Distinctive:

    Run recipe and tool checks that depend on the schema.

    line 24

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Device Schema Extraction

Use this skill when populating src/knowledge/devices, indexing packs or changing scripts/extract-device-schemas.mjs.

Sources

  • Bridge introspection of device.parameters for name, min, max, default and automation flags.
  • Default.adv parsing for saved default state.
  • Ableton manuals and LOM docs for behavior notes.
  • Manual curation for units, nonlinear curves, macro targets and useful descriptions.

Workflow

  1. Extract or introspect raw parameters.
  2. Normalize slug, id, category, vendor and Live version metadata.
  3. Fill min, max, default, unit, automatable, modulatable and concise description.
  4. Mark source and completeness.
  5. Validate uniqueness of ids, names and indexes.
  6. Run recipe and tool checks that depend on the schema.

Quality Rules

Descriptions must be short, English and useful to an LLM. Do not invent ranges. Use unit=curve for nonlinear 0..1 controls and explain audible behavior. Keep runtime-discoverable facts out of static knowledge unless they are slow-changing and useful.

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