check_coverage

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

No annotations are provided, so the description bears the full burden of disclosing behavior. It only states the nominal result (which tickers are covered) and gives no indication of side effects, error conditions, or what happens with invalid or unknown tickers. For a tool without annotation safety hints, this is a meaningful transparency gap.

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 a single concise sentence with no filler. It communicates the core idea in eight words. It is slightly awkward grammatically ('the current model build covers') but remains compact and easy to scan.

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 low complexity (one parameter, no output schema, no annotations), a brief description is acceptable. However, the absence of any detail about the return format or expected ticker format makes it minimally viable rather than complete. An agent could call it correctly with reasonable assumptions, but the margin for misinterpretation is non-trivial.

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 beyond the schema. It mentions 'given tickers' but does not explain what constitutes a valid ticker, case sensitivity, or how to interpret coverage. The parameter name and type are obvious from the schema, but the description contributes little additional semantic value.

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 the query action: it identifies which tickers are covered by the current model build. Though phrased as a fragment rather than an imperative verb, the resource (tickers, model build) is clear and distinct from sibling tools like get_factor_exposures or stress_test. It could name the outcome more explicitly, but it is far from tautological.

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?

There is no guidance on when to use this tool versus its siblings. No context suggests that this should be called before factor exposure or risk computations, and no alternatives are mentioned. An agent must infer the use case from the name and description alone.

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