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

No annotations are provided, so the description carries the full burden. It discloses the output structure, the meaning of silent statuses, the coverage_summary fields, and the 5min cache. It implies a read-only operation without stating side effects, which is acceptable for a read tool, but it doesn't explicitly mention authorization or error behaviors.

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 plus a cache note, each sentence delivering specific, non-redundant information. It is front-loaded with the primary purpose and then adds details about output and usage. No wasted words.

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 simplicity (one parameter, no output schema), the description fully covers the return values: per-voter fields, statuses, the why explanation, coverage_summary contents, and the 5min cache. It also provides a clear trigger for use, making it complete for an agent to select and invoke correctly.

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 input schema already provides a description for the single 'ticker' parameter (100% coverage). The tool description adds no further parameter semantics beyond the phrase 'Per-ticker,' which is also in the name. Baseline 3 applies because the schema does the heavy lifting.

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 identifies the tool's purpose: per-ticker accounting for every voter in the 19-voter ensemble, returning score, baseline weight, status, and a why explanation for silent voters. It distinguishes itself from sibling tools like voter_attribution and voter_ic_drift by focusing on coverage statuses and upstream data pipelines.

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 usage context: 'Use this when a model_prediction shows low voter_coverage — it tells you exactly which data pipelines to wake up.' It tells the agent when to use it but does not explicitly mention alternatives or when not to use, so it falls short of a 5.

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