ppt_check_ai_ocr

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'probes' something but does not reveal whether it performs network requests, what side effects exist, what it returns, or any authentication requirements. This is a significant gap.

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 a single sentence with no filler, which is concise. However, it is under-specified rather than efficiently complete, leaving out crucial context that would make it a high-quality tool description.

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 six parameters and no annotations, the description is wholly insufficient for an agent to understand the tool's behavior, inputs, or expected output. Even though an output schema exists, the description does not explain what the probe actually checks or how to interpret results.

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 schema has 0% description coverage for parameters, and the description mentions none of the six parameters (api_key, model, options, base_url, provider, ocr_ai_chain_mode). The description adds no meaning beyond the bare parameter names, so it fails to compensate for the lack of schema descriptions.

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 uses a specific verb ('Probe') and a target resource ('the current AI OCR chain'), which suggests a validation/testing purpose. However, 'whether a model can work' is vague and does not define what success or failure looks like, nor does it clearly differentiate from sibling tools like ppt_health_check or ppt_check_route.

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 offers no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or context. It only states what it does at a high level, leaving the agent to guess when this tool is appropriate.

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