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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context: the token budget, the percentile-based framing, the four panel names, the composite P3 score, and the inclusion of curated peers. This goes well beyond what the annotations alone convey, with no contradiction.

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 dense but efficient, front-loading the core outcome ('The character of one stock in ~550 tokens') before listing components and ending with use cases. Every clause contributes useful information, and nothing is redundant with the schema.

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?

With no output schema, the description carries the burden of explaining return values, and it does so well by enumerating the major output sections. It could be slightly more explicit about interpretation or edge cases, but for a read-only, single-parameter tool with 100% schema coverage, it is adequately complete.

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 100%, so the schema fully documents the parameters. The description adds minimal parameter-specific meaning beyond implying a single stock context; it does not describe as_of or ticker semantics in further detail. Baseline 3 is appropriate.

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 defines what the tool produces: a ~550-token 'character' of one stock composed of 16 percentile scores, four panels, a composite P3 score, curated peers, a character read, and a price line. It also distinguishes itself from siblings by emphasizing 'one stock' and 'vs the S&P 500 cohort' and explicitly noting 'not GICS.' This is a specific, informative statement of purpose.

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 gives explicit use cases: 'Use for "is this number good?" and quick company character.' This tells an agent when to invoke it, though it does not explicitly name sibling alternatives or state when not to use it. The context is clear enough for a single-stock read tool.

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