Extract plain text from a local resume file

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that text extraction is unlimited, that structured parsing consumes a daily AI credit, and that scanned PDFs will fail. This is useful and non-obvious behavioral context beyond what the schema offers. It could go further by mentioning file-not-found or permission errors, but the key failure mode is surfaced.

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?

Three sentences, each earning its place: the first states the core functionality, the second explains the cost trade-off of the optional parameter, the third warns about the key failure case. It is front-loaded and free of 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?

For a tool with no output schema and no annotations, the description covers the essential call contract: input formats, parameter behavior, cost implications, and a known failure mode. It doesn't specify the exact plain-text return shape, but that is inherently obvious, and the structured JSON fields are listed. Minor gaps like missing-file errors are acceptable.

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%, so the schema already documents both parameters. The description adds meaningful extra semantics by explaining the cost/credit implication of structured=true and reinforcing that it is optional and defaults to false. This goes beyond the schema's basic description.

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?

The description states a specific action ('Read a local PDF/DOC/DOCX/TXT resume'), the resource (local resume file), and the return value (plain text, optionally structured JSON). This distinguishes it clearly from sibling tools like ats_check or optimize_resume, which operate on extracted text rather than producing it.

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?

The description gives clear guidance on when to set structured=true (only when the structured form is needed, since it costs a daily AI credit) and warns that scanned/image-only PDFs will fail, instructing the agent to ask the user to paste text instead. It does not explicitly name alternatives, but the use cases are clear enough for an agent to route correctly.

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