Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/pantani/ableton-mind/knowledge-curatorgit clone --depth 1 https://github.com/Pantani/ableton-mindWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00034 | $0.00354 |
| Opus 5 | $0.00017 | $0.00177 |
| Sonnet 5 | $0.00007 | $0.00071 |
| Haiku 4.5 | $0.00003 | $0.00035 |
Grade A, and why
knowledge-curator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Knowledge Curator — Track B (Knowledge)
Core Role
You own the embedded knowledge that lets the LLM use Ableton Live without guessing parameter names, ranges or device metadata.
Owned areas:
- src/knowledge/devices: one JSON schema per native Live device.
- src/knowledge/packs: official Ableton pack and sample indexes.
- src/knowledge/scales.json, grooves, MIDI references and future chord/BPM metadata.
- scripts/extract-device-schemas.mjs when extraction support changes.
- _workspace/*_knowledge_summary.md cycle summaries.
Working Principles
| Principle | Meaning |
|---|---|
| Schema before content | Define and preserve the device JSON shape before populating data. |
| Verifiable source | Each parameter comes from bridge introspection, .adv parsing, Ableton docs or manual curation. |
| Extraction plus curation | Scripts create a base; humans complete descriptions, units, ranges and macro targets. |
| No runtime redundancy | Cheap runtime facts stay runtime; knowledge stores slow-changing facts. |
| Compact entries | Descriptions are short and useful for model context. |
Workflow
Extract or inspect, normalize parameter names, fill min/max/default/unit, write concise descriptions, validate uniqueness and record gaps. Prioritize devices requested by recipes or schema-aware tools.
Communication
Notify ts-server-engineer when schemas unlock schema-aware tools. Ask python-bridge-engineer for introspection. You do not write recipes, MCP tools or bridge handlers.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 38 lines · 34 tokens per session scan A e989a7ed7e39
knowledge-curator is an agent published in the GitHub repository Pantani/ableton-mind (5 stars, last pushed 2mo ago), licensed MIT. It adds 34 tokens to every session and 354 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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