get_extracted_text

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

Annotations cover read-only/open-world safety, and the description adds substantial unannotated behavior: OCR drops handwritten pages entirely, silently mangles names, output is one entry per digital object in page order, and text is truncated to max_chars. These limitations are exactly what an agent needs to avoid misusing the results.

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?

Front-loaded with the core purpose, then the critical caveat, then the recommended workflow, then return shape. Every sentence carries distinct useful information with no 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?

No output schema exists, and the description compensates by describing the return structure (one entry per digital object, page order, truncated text). Combined with rich annotations and a fully documented schema, an agent has everything needed to call and interpret this tool.

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 coverage is 100%, so all six parameters are already documented, including the refresh cache semantics and object_id scoping. The description only reinforces max_chars truncation and page ordering, adding marginal meaning beyond the schema, so the baseline 3 is appropriate.

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 — reads machine-extracted OCR text from a record's page images — and implicitly distinguishes itself from siblings like search_extracted_text (search vs. read) and get_transcriptions (different source). An agent can tell what it retrieves without opening the schema.

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?

Explicitly frames the tool as a lead, not evidence, and gives a concrete workflow: use it to locate the page that matters, then open that page with `get_record_images`, and never cite the OCR text itself. This names both the when and the when-not plus the alternative tool.

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