| name | assess |
| description | Check whether text matches a natural-language condition. Returns "true" or "false". Auto-chunks long texts and short-circuits on first match. |
| args | {"source":"required string — text to evaluate (a `$stepN` binding or a literal)","predicate":"required string — natural-language condition (e.g. \"is critical of the author?\", \"mentions specific dates?\")"} |
assess
Boolean test of text content against a natural-language predicate. Returns the literal lowercase string "true" or "false".
Behavior
- Texts longer than 16k characters are split into chunks at sentence boundaries.
- Returns
"true" on the first matching chunk (short-circuit). Returns "false" only if all chunks fail.
- Returns
"false" on ambiguous LLM responses (no half-credit).
Planning notes
Phrase predicates to detect presence rather than global summary, because chunks are evaluated in isolation:
- Good:
"contains mention of inflation?"
- Risky:
"is the main topic inflation?" — a chunk that briefly mentions inflation might match even if it isn't the main topic of the whole document.
Every chunk requires an LLM call, so very long inputs are expensive.
Example
{"thought": "check if the article is critical of the proposal", "tool": "assess", "source": "$step1", "predicate": "is critical of the proposed policy?"}
