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

With no annotations, the description carries the full disclosure burden and does so: it documents case/punctuation-insensitive matching with stopword dropping, ranking order, the 'ambiguous' flag and required user clarification, the historical fallback with match = former_or_closed, the single 'no_match' row, and the quarter coverage range. This is far beyond what the schema conveys.

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 core purpose, then layers matching semantics, ranking, fallback behavior and downstream routing in a single dense narrative. Every sentence earns its place, though the length approaches the point where structure (e.g. short bullet-like clauses) would aid scanning.

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 an output schema exists, return-field enumeration is redundant but harmless; the description nonetheless covers every edge case an agent must anticipate — ambiguous matches, historical fallback, and the no-match sentinel. Nothing needed to call and interpret this tool correctly is missing.

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 0%, so the description must compensate. It explains name matching mechanics, quarter defaulting to latest, and how city/state disambiguate results, but 'limit' (default 15) is never mentioned and the accepted quarter string format is left implicit. Partial compensation merits the baseline 3.

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 and resource ('Find FDIC-insured banks') plus the scoping facets (name, state or city, quarter) and the data domain (domestic FDIC-insured filers, 2018-03 to 2026-06). An agent can distinguish it from find_credit_union purely from the text.

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?

Gives concrete routing guidance: use the returned cert in bank_quarter_income, bank_metric_series and bank_peer_compare, and instructs the agent to ask the user when 'ambiguous' is true rather than picking the first row. It stops short of an explicit when-to-use-this-vs-find_credit_union contrast, so it is a strong 4 rather than a 5.

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