compute_screening_metrics

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

Without annotations, the description fully discloses behavior: the computation is done in code, the output structure (metrics with `meaningful` and `caveat`, `flags`, `data_quality`), and warnings against recomputation. No contradictions.

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 front-loaded with purpose and lists metrics and usage instructions. While detailed, it is relatively well-structured and each sentence adds value, but could be more concise.

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 no output schema, the description thoroughly explains the output structure and usage. However, it fails to explain input parameters, which are essential for correct invocation, making it somewhat incomplete.

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% and the description does not explain the parameters `query` or `years`. The context implies `query` is the screen result and `years` is the time horizon, but this is not explicit, leaving the agent to guess.

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 computes screening metrics and flags from a screen result, listing specific metrics and flags. It distinguishes from sibling tools which focus on data retrieval rather than computation.

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 explicit instructions on how to use the output (e.g., respect `meaningful` boolean, report flags verbatim, do not recompute). However, it lacks explicit guidance on when to invoke this tool versus alternatives, though the context of requiring a screen result is implied.

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