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

Annotations already declare readOnlyHint=true, and the description adds useful behavioral details: it is 'Precomputed, deterministic' and explains the exact return structure (full counts plus per-ticker tiles with tags). This goes beyond the annotation without contradicting it, giving the agent confidence in consistency and performance.

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 moderately long but every sentence contributes: it front-loads the purpose, defines the states, outlines the return payload, and explains the strategic value. It could be trimmed slightly (e.g., the closing 'proves coverage' sentence is more persuasive than informative), but it remains focused and well-structured.

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?

For a zero-parameter tool with an output schema, the description is exceptionally complete. It explains all possible thesis states, what tags accompany each category, and the broader rationale. The presence of an output schema reduces the need to document return values, and this description fully covers everything else an agent needs to know.

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 tool has zero parameters, so there is nothing for the description to elaborate on. The baseline for zero params is 4, and the description appropriately focuses on behavior rather than parameterization. No additional parameter semantics are needed.

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 opens with a specific verb-plus-resource statement: 'every covered company's current thesis state on one wall.' It enumerates the four possible states and indicates what the tool returns. It clearly distinguishes itself from siblings by covering the whole market rather than a single entity or metric, so an agent knows exactly what this tool is for.

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 conveys that this is for a market-wide overview ('Shows the whole market at a glance') and implies it is the go-to for a high-level health check. It does not explicitly name alternative tools or specify when not to use it, but it gives enough context about its scope to make appropriate routing likely.

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