| name | generate-note |
| type | python |
| description | Generate new text or code content from scratch using natural language prompt via LLM. Creates content from the LLM's own knowledge — no source documents. |
generate-note
LLM-based content generation. Creates new text or code from scratch using natural language instructions.
No source documents — for generation from source material, use synthesize instead.
Input
prompt: Generation instruction (required)
style: "code" or "text" (optional, default: "text")
target_tokens: Integer (optional). Target output length in tokens. Overrides default max_tokens when provided via OUTPUT GUIDANCE.
Output
Success (status: "success"):
value: Generated content (text or code)
Failure (status: "failed"):
reason: Error description
Behavior
- text (default): Generates prose, summaries, explanations (temperature=0.7)
- code: Generates code with stricter formatting (temperature=0.2)
Planning Notes
- Use for creating NEW content from scratch (no source material)
- Use
extract for deriving content from a single Note
- Use
synthesize for integrating content from multiple documents
- Do NOT pass context — use
synthesize with source Collections instead
Examples
{"type":"generate-note","prompt":"Write a Python fibonacci function","style":"code","out":"$fib"}
{"type":"generate-note","prompt":"Explain quantum computing basics","out":"$explanation"}