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

No annotations are provided, so the description carries the full burden. It says nothing about cost/latency of OCR, size limits on URL or base64 input, what happens on unsupported languages or malformed page ranges, or what the return value looks like. Only input semantics are covered.

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?

One front-loaded purpose sentence followed by a tight per-parameter list; no filler. Slightly terse on paginas format, but every sentence earns its place.

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 3-parameter tool with no annotations and no output schema, the parameter documentation is adequate, but the description leaves output shape, error/language-failure behavior, and input size constraints unaddressed. It is the minimum viable description for correct invocation.

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 0%, so the Args block does the work and does it well: fuente is a public URL or base64 content, idioma is a tesseract language code with concrete examples (spa, eng, spa+eng), paginas is an optional PDF page range defaulting to all. The only gap is the exact range syntax (e.g. '1-5').

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 concrete verb and resource: recognize text from a scanned PDF or image. That is specific and unambiguous. It does not differentiate itself from the sibling pdf_texto (digital-PDF extraction) or pdf_markdown, so an agent must infer that OCR is for scans/images rather than born-digital text.

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?

Implies the use case by naming 'scanned PDF or image', but never states when to choose this over pdf_texto, pdf_markdown or pdf_tablas, nor any prerequisites (language availability, base64 size limits). No explicit when/when-not guidance for a crowded sibling set.

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