journal_introspect
Ask your journal a self-question. Retrieves relevant entries and generates a grounded answer in your first-person voice, with hallucination risk score. Returns 'no patterns found' if entries are insufficient.
Instructions
Ask YOUR journal a self-question. Pulls semantically-relevant entries, then asks the configured LLM to answer in YOUR first-person voice grounded ONLY in those entries (no invention). Returns the answer plus entries_referenced and a hallucination_risk score (high if <3 entries grounded the answer, medium if <6, otherwise low). If entries don't support an answer, the answer literally is "no patterns found in journal".
Tool call template
Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {
"question": "<question>"
},
"name": "journal_introspect"
}
}Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | A self-question (e.g. "Have I been more cautious lately?"). | |
| scope | No | recent (last 14 days) | all (default). |