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

With no annotations, the description bears the full burden. It implies a safe, static read by saying it 'returns' data, and it names the payload contents. It does not state whether the data is static or refreshed, whether auth is required, or how large the result is, so gaps remain.

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?

A single front-loaded sentence with no filler. Every word ('complete offer ladder', 'canonical public URLs') carries meaning about the payload.

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?

For a zero-argument read tool with no output schema, the description is adequate but thin: it does not describe the shape of the offer ladder or what the canonical URLs point to, so the agent cannot anticipate the response structure.

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 tool takes zero parameters, which is the baseline-4 case. There is nothing for the description to clarify, and the empty schema is unambiguous.

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?

States a specific verb (Return) and a specific resource (AIT Advisory's complete offer ladder and canonical public URLs). An agent immediately understands the payload. It does not, however, differentiate itself from siblings such as get_diagnostic_details, which also appear to return catalog-style data.

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 gives no indication of when to call this versus assess_company_fit, get_diagnostic_details, or start_diagnostic_purchase, nor any prerequisites. Usage must be inferred purely from the name and the returned artifact.

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