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

No annotations exist, so the description carries the full burden for behavioral disclosure. It clearly implies a read operation and highlights the data fields, but does not disclose potential gotchas like historical coverage depth, data update frequency, pagination behavior, or permission requirements. It adds some context ('alternative-data', CEO + named officers) but lacks rich behavioral detail expected without annotations.

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, front-loaded with the core purpose, and every phrase adds value. It efficiently lists the return fields and gives usage examples without unnecessary fluff. No redundancy or irrelevant details.

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?

There is no output schema, so the description must explain return values; it does so by listing all expected fields (name, role, year, salary, etc.). For a simple list retrieval tool with one required param and one optional param, this level of detail is quite complete. Minor gaps like output format (array/object) or historical depth limits exist, but not enough to knock it below a 4.

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 50%: only 'ticker' has a description, and that description is generic ('Path parameter'). The description reinforces that a ticker is needed ('for a ticker') but says nothing about the 'limit' parameter, its default, or its purpose. Since coverage is below 80%, the description needed to compensate, and it only partially does for ticker while ignoring limit entirely.

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 provides annual executive compensation history for a ticker, specifying CEO plus named officers and the exact fields returned (name, role, year, salary, bonus, stock_option_awards, total_compensation). It uses a specific resource ('executive compensation history') and differentiates itself from siblings like insider trades or governance tools. The phrase 'alternative-data' adds context that this is a distinct data source.

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 explicit usage triggers: 'Call this when the user asks "how much is the CEO paid?" or wants pay-vs-performance context.' This provides clear 'when to use' guidance. However, it does not mention when not to use or name alternative tools, falling short of the full 'when/when-not/alternatives' guidance for a top score.

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