pdf_to_markdown

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

No annotations exist, so description carries full burden. It discloses that the tool converts PDFs, returns multiple data fields (markdown, counts, summary), but omits behaviors like error handling, rate limits, or file size constraints.

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?

Two sentences, front-loaded with action and output, followed by use cases. No redundant words, highly efficient.

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 an output schema present, return values are covered. The description lists return components. For a two-parameter tool, it's mostly complete, but could explicitly tie the summarize parameter to the summary output.

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 0% for parameters, so description must add meaning. It mentions 'via URL' but doesn't specify URL requirements. The boolean 'summarize' is implied by the output mention of 'AI summary', but not explicitly linked. Adds partial context.

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 clearly states the action ('Convert any PDF document via URL to clean Markdown'), lists output components, and specifies use cases (whitepapers, reports, etc.), distinguishing it from unrelated siblings.

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?

It provides explicit use case examples ('whitepapers, reports, contracts, or research papers'), giving context for when to use. However, no direct exclusions or alternatives are mentioned, though none are needed given sibling diversity.

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