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

With no annotations provided, the description carries the burden of behavioral disclosure. It adds valuable context: 'Default output summarizes meta keys; full meta requires a reason' describes output behavior and a conditional requirement not apparent from the name alone. The add-on note also discloses potential non-availability. However, it does not mention pagination behavior or response format details, leaving some aspects unexplained.

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 two sentences long, with the primary purpose in the first sentence and key behavioral notes in the second. Every clause adds value: 'List Lever audit events for security and access investigations' states purpose, 'This endpoint is a Lever add-on' adds availability context, and 'Default output summarizes meta keys; full meta requires a reason' describes output behavior. No filler or redundancy.

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 tool's complexity (10 parameters, no output schema) and the absence of annotations, the description provides the most critical context: purpose, availability, and output behavior. It does not explain pagination or response structure, but the schema already details the cursor parameter and the description mentions meta key summarization. For a list tool with a well-documented schema, this level of completeness is above average.

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 description coverage is high (90%), and the schema already documents all parameters with clear descriptions, including enums and defaults. The description adds minimal parameter-specific meaning beyond the schema; the 'meta keys' and 'reason' references partially relate to detail_profile and reason, but these are already covered in the schema. Thus, a baseline score of 3 is appropriate—the schema carries the load, with only marginal added 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 starts with 'List Lever audit events for security and access investigations,' which uses a specific verb ('List'), a clear resource ('Lever audit events'), and a purpose ('security and access investigations'). This distinguishes it from all sibling list_* tools, which target other resource types. The mention of 'This endpoint is a Lever add-on' further clarifies its unique position.

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 context for when to use the tool ('for security and access investigations') and includes important usage caveats: 'This endpoint is a Lever add-on' implies availability constraints, and 'full meta requires a reason' sets a prerequisite. It does not explicitly mention alternatives or when not to use it, but no direct alternatives exist among the sibling tools, so the guidance is adequate.

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