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

Without annotations, the description carries the burden. It discloses the data source (Supabase, no invented values) and error type. It implies a read-only operation via 'look up'. This adds useful context beyond the schema, though more details on authentication or rate limits would help.

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 three sentences, no wasted words, and front-loads the purpose. Every sentence adds value (purpose, return content, data provenance, error handling).

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 an output schema exists (not shown), the description need not detail return fields, but still summarizes them well. It mentions error cases and data source. Minor omission: does not specify that only one fiscal year is returned or that the tool may not support multiple years. Overall sufficiently complete for a lookup tool.

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 add meaning. It explains that fiscal_year defaults to the latest available if omitted. However, it does not describe the ticker (beyond implying it's a company identifier) or the agent_token parameter, leaving some semantics to be inferred.

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 looks up executive compensation for a company, specifying the coverage universe and return values (CEO/NEO total compensation, pay mix, canonical metrics). It does not explicitly differentiate from siblings like benchmark_executive_pay, but the verb 'look up' and scope are specific enough.

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 on when to use (for companies in coverage) and error behavior for out-of-coverage tickers, but does not give explicit guidance on when not to use or compare with siblings such as benchmark_executive_pay.

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