clinical_ai_inspect

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

No annotations exist, so the description bears full responsibility for disclosing behavioral traits. It does not mention whether the tool is read-only, what happens on invalid inputs, authentication needs, rate limits, or any side effects. The listed content categories hint at output but not behavior.

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 run-on sentence that packs many categories with slashes and parentheses. While it front-loads the core purpose, the structure is dense and could be clearer (e.g., using bullet points). It is not excessively long but lacks readability.

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 the lack of annotations and output schema, the description should cover input usage, output format, and behavioral context. It only describes the summary content, leaving the agent without critical information about how to invoke the tool and what to expect.

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 2 parameters (url, document_json) with 0% description coverage, and the tool description does not mention these parameters at all. The agent receives no guidance on how to use url versus document_json or what formats are expected.

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 tool produces a 'Structured summary of a Clinical AI Card' and enumerates the specific categories covered (system identity, clinical context, regulatory posture, etc.). This is a specific verb+resource combination that distinguishes it from siblings like clinical_ai_fetch (fetch raw card) or clinical_ai_validate (validate).

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 provides no guidance on when to use this tool versus alternatives. It does not mention that clinical_ai_fetch retrieves raw data or that clinical_ai_validate checks validity. The agent must infer usage without any explicit context about tool selection.

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