# Assess

> Check whether text matches a natural-language condition. Returns "true" or "false". Auto-chunks long texts and short-circuits on first match.

- Skill: `bdambrosio/assess` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add bdambrosio/assess`
- Raw SKILL.md: https://api.skillmd.com/api/skills/bdambrosio/assess/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: bdambrosio (https://skillmd.com/u/bdambrosio)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/bdambrosio/assess

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# 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

```json
{"thought": "check if the article is critical of the proposal", "tool": "assess", "source": "$step1", "predicate": "is critical of the proposed policy?"}
```