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

Annotations already cover the safety profile (readOnly, idempotent, non-open-world), so the description's job is to add context — it does so with case-insensitivity, partial matching, and the explicit warning that definitions describe concepts and never state a program parameter, which prevents misuse.

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?

Three short sentences, front-loaded with what it is, then how to call it, then the scope caveat. No 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?

For a single-parameter, fully annotated, read-only lookup with no output schema, the description covers identification, both call modes, matching rules, and the notable limitation that no definition contains program parameters. Nothing needed to call it 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 coverage is 100% and already documents the single optional 'term' parameter, so the baseline is 3; the description adds matching semantics (case-insensitive, partial matches accepted) that the schema does not specify.

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 (look up / list) and resource (DSCR and investor-loan glossary, 26 terms), which is immediately distinguishable from sibling tools like loan_programs or rate_ranges that return program data rather than definitions.

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?

Clearly describes both invocation modes (pass a term vs. omit to list all) and matching behavior, giving an agent enough to pick the right call. It stops short of naming an alternative tool for program parameters, though the final sentence implies that boundary.

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