pdfhell_run

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

With no annotations provided, the description fully carries the burden. It discloses that it runs a benchmark, calls external APIs using environment variables (with keys like ANTHROPIC_API_KEY), and that keys are not logged. It also describes the return value structure. This provides good behavioral insight, though it does not explicitly state non-destructive or rate-limit behaviors.

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?

The description is well-structured with 'Args' and 'Returns' sections, making it easy to parse. It uses bullet points for suite options and includes example formats for model. Every sentence provides useful information; there is no fluff. It is appropriately sized for the tool's complexity.

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?

Given that an output schema exists, the description needs not detail return values fully. However, it does summarize the return dict and notes that suite version/hash are included. It covers the tool's purpose, all parameters with defaults, and additional context about environment variables. The description is complete for this tool's context.

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?

The input schema has 0% description coverage, so the description must compensate. It does so excellently: model format with examples, suite options with case counts and cost estimates, and workers with default. This adds significant meaning beyond the raw schema types. Every parameter is explained with concrete details.

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 starts with 'Run the pdfhell adversarial-PDF benchmark against a vision model,' which clearly states the verb (run) and resource (adversarial-PDF benchmark). This distinguishes it from sibling eval_* tools and pdfhell_make, all of which have different purposes. The purpose is specific and immediately understandable.

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?

While the description explains what the tool does and details the parameters, it does not explicitly guide when to use this tool versus alternatives like pdfhell_make or other eval tools. It implies usage when running a pdfhell benchmark, but no explicit when-to-use/when-not-to-use guidance is provided. The lack of differentiation from siblings limits the score.

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