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

Annotations already declare this is a safe read-only operation. The description adds useful behavioral context by stating that results include severity and debiasing recommendations, and it discloses a concrete cost of 20 credits per call. It does not cover rate limits or authentication, but it goes beyond the annotations meaningfully.

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 short and front-loads the core purpose, return contents, and cost. The fragment 'UNDERSTAND.' is slightly ambiguous, but overall the wording is efficient and does not waste space.

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?

The output schema exists and annotations cover safety, so return details and behavioral safety are largely handled elsewhere. However, with 0% schema description coverage, the description should do more to explain 'goal' and 'session_id' and to clarify when this tool should be chosen over siblings.

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 0%, so the description must explain the parameters, but it only implies that 'text' is the content to analyze. It gives no meaning for the optional 'goal' or 'session_id' parameters, leaving two of three parameters undocumented.

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 states a specific verb and resource: finding cognitive biases in messaging, UX copy, or product framing. This is clearly distinct from siblings like write_product_copy or find_hidden_barriers, so an agent can identify the tool's purpose without opening the schema.

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 implies usage by naming the contexts where the tool applies: messaging, UX copy, and product framing. However, it does not explicitly say when to use this tool versus alternatives such as find_hidden_barriers or write_product_copy, leaving routing partly to inference.

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