Evaluate text, project files, images or PDF pages against caller-defined predicate, choice or score questions. Batch independent questions about shared evidence. Use paths instead of copying files. Returns compact answers and coverage; full=true includes all probabilities. Makes a paid OpenAI API request.

Apply common typed questions independently to up to 20 named items, each containing text or file/image/PDF sources. At most 3 evaluations run concurrently. Returns per-item results/errors in input order; never replays successful items. Paid requests: one per valid item. Caller chooses the criteria and subsequent selection.

Locate relevant code within caller-supplied project files or line ranges. Evaluates every 200-line chunk with 20-line overlap, returns paths/ranges and relevance probabilities without code text. Discover candidate paths with your normal file listing first. Maximum 20 chunks and 1 MiB total text; oversized scopes fail before any paid call. One paid request per chunk, up to 3 concurrently. Returns every result, refusal and error; no automatic filtering or Read hook. Independent chunks cannot establish cross-file behavior.