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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It reveals the pricing ($1.00 per call) but does not explain what the tool returns (e.g., a report, a pass/fail status, or a list of vulnerabilities), nor does it mention side effects, permission requirements, or whether it modifies the input. This lack of transparency is critical for an audit tool.

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 consists of three concise sentences. The first sentence states the core purpose, the second provides the usage context, and the third gives pricing. Every sentence adds valuable information without redundancy or fluff, making it efficient and front-loaded.

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?

Despite having 6 parameters and no output schema, the description omits many details needed for an AI agent to use the tool effectively. It does not explain how to interpret the results, what each parameter does beyond the schema, or any dependencies (e.g., subscription token usage). The tool's complexity demands more context, especially regarding the output format and behavioral expectations.

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 6 parameters with 100% description coverage, so the schema already documents each parameter. The description adds no extra meaning beyond mentioning 'agent configuration' (the config parameter). Since the baseline is 3 when schema coverage is high, and the description does not degrade or improve understanding, a score of 3 is appropriate.

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's purpose: 'Audit an AI agent configuration for security holes: prompt injection exposure, missing authentication, over-broad tool permissions and unsafe gateway settings.' It specifies the verb (audit/check) and the resource (AI agent configuration), and the specific security aspects differentiate it from the sibling tools (e.g., base_token_verification, web_application_verification).

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 a clear usage scenario: 'Check an agent before you trust it or connect to it.' This tells the agent when to invoke the tool. It also mentions the cost ($1.00 per call), which is relevant for decision-making. However, it does not explicitly state when not to use it or compare it to sibling tools, missing the opportunity to provide exclusions or alternatives.

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