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

Annotations already declare read-only, idempotent, open-world, non-destructive behavior, so the safety profile is covered. The description adds genuinely useful context beyond that: no caller authentication is needed and the scope is aggregate statistics only, not individual bond transactions.

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?

Front-loaded with the verb and resource, then the scope and usage instruction, then a clarifying exclusion and example. The long enumeration of dataset families is somewhat dense but defensible for a catalog tool where the list is the point.

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 describing the return value and does so: it explains the response contains the key to pass to other tools, what each series measures, and the date field each is filtered on. An agent knows exactly what it gets and why to call it first.

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?

Zero parameters, so the baseline is 4; the description correctly notes the call takes no arguments (example shows an empty object) and that it is keyless for the caller. Nothing further is required of a parameterless catalog tool.

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?

States a specific verb (List) and resource (FINRA fixed income aggregate datasets), then enumerates the concrete series families covered. It clearly distinguishes itself from finra_fixed_income_series by scoping to aggregate market statistics rather than individual transactions or series-level data.

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?

"Call this first to see what US bond-market data can be queried" gives explicit ordering guidance and positions the tool as the discovery entry point whose key is passed to other tools. It stops short of naming finra_fixed_income_series as the follow-up, leaving the agent to infer the pairing.

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