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

The annotation only provides openWorldHint=true, so the description carries the burden. It discloses that the tool queries period changes based on specific company names and clarifies the scope and exclusions. It also mentions the pricing per run. However, it does not disclose potential variability in results due to differing data availability across countries or time periods, which could be relevant.

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 well-structured with clear sections for purpose, metrics/types included, exclusions, and typical query examples. It is concise and front-loaded with the main purpose. The pricing information is appended but useful. No extraneous content, though it could be slightly more compact.

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 moderate complexity (2 parameters, no nested objects, output schema exists), the description provides sufficient context including what it covers and what it does not, and examples. The output schema exists so return values don't need detailed explanation. The only gap is minor behavioral nuance about data availability, but overall it's complete.

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 schema covers 100% of parameters, with examples for each parameter in the input schema and typical query examples in the description. The description reinforces the meaning of company_name and country_name but does not add substantial new semantics beyond what the schema provides, so baseline 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 queries period changes in employer brand aspects based on a specific company name, specifically entrepreneur education, social positions, and personal honors. It distinguishes itself by stating it does not perform executive departure/transfer or negative sentiment queries, though it could be more explicit about its unique status among the many enterprise_change_* siblings.

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 explicitly lists what it is used for (querying entrepreneur education, social positions, personal honors), what it does not include (non-category indicators, batch filtering by park/industry chain), and provides typical query examples with full company names and country names. This clearly guides when to use this tool versus alternatives like enterprise_change_executive_change or enterprise_change_executive_sentiment.

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