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

Beyond the annotations, the description discloses detailed behavior: ranking order, case-insensitivity, default and maximum limit, no HTTP beyond cached assets, and the fields returned. This gives the agent a clear model of what will happen when the tool is invoked.

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 every sentence carries value: scope/ranking, limit/result fields, and a concrete example. It is front-loaded with the core purpose and avoids filler.

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?

The tool is simple with two parameters and an output schema, and the description covers the query semantics, limit behavior, ranking, and result contents. Nothing essential is missing for an agent to call it 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?

Despite the 0% schema description coverage, the description fully explains both parameters: query is matched against symbol/name with an example, and limit has a default of 10 and a cap of 50. It adds meaningful behavior that the bare input schema does not convey.

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 a specific verb and resource: 'Local fuzzy search over the token list'. It also distinguishes itself from the sibling tools by emphasizing it is local and requires no HTTP beyond cached assets, which differentiates it from tools like quote or price_history.

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 clearly communicates that this tool is for fuzzy searching tokens by symbol or name, with ranking rules and an example. It does not explicitly name sibling alternatives or state when not to use it, but the local-search context is strong enough for an agent to select it appropriately.

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