search_extracted_text

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare the safe read-only, open-world profile, and the description goes well beyond them: results are machine output, not evidence; handwriting is missed; names are mangled; hits are probabilistic rather than authoritative. That is exactly the kind of accuracy caveat an agent needs before asserting a match.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded in one sentence, followed by a tight caveat block; each sentence earns its place. The corpus-scoping sentence is slightly clause-heavy but still informative rather than filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description adequately covers the source corpus, the trustworthiness of results, and the verification step. It does not sketch the returned record shape, but the surrounding get_record/get_extracted_text siblings make that omission minor.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% (page, limit, query syntax all documented in the schema), so baseline 3 applies. The description adds no query-syntax or pagination detail beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (“Find records whose extracted text mentions something”) and scopes the corpus as the machine-generated searchable OCR layer beneath the page scans, which implicitly separates it from transcription- and tag-oriented siblings. It never names the near-neighbour tools (search_transcriptions, search_by_contribution_text), so an agent must still infer which search surface applies.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives strong guidance on how to treat results (“read the page image before citing anything you find here”), which implies download_page_image as a follow-up step. It does not say when to choose this tool over the sibling search tools, so selection between search surfaces remains implied rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.