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

With no annotations, the description carries the full burden and does so unusually well: it discloses the derivation method (consecutive YTD 5300 reports, Q1 = reported YTD), the continuity_status taxonomy, and that unverified_no_adjacent_prior rows return null values with a reason. It does not cover auth/permission requirements or date-string input formats, keeping it short of a 5.

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?

Dense but every sentence contributes: payload fields, date span, argument pattern, derivation, and the continuity_status semantics. Front-loads purpose before the caveats, though the prose is long and could be tightened into list form.

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?

No output schema exists, and the description picks up that burden by naming the returned measures and the continuity_status columns plus their meaning (verified / event_contaminated / unverified_no_adjacent_prior). Missing only input date formats and the exact shape of event metadata fields.

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% and all four parameters are bare titles, so the description must compensate. It does define the roles of cu_number, quarter (with default latest) and start/end (mutually exclusive with quarter), but gives no format guidance for quarter/start/end strings, so an agent can still guess wrong.

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?

Specific verb+resource: single-quarter income for one credit union, with the exact fields returned (net income, interest/noninterest income and expense) and the date span (2018-03 to latest). It explicitly distinguishes itself from siblings by contrasting with bank_quarter_income (credit union vs bank) and by stating 'no rankings or trailing totals here' (i.e. not peer_compare/metric_series).

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?

States the selection rule concretely: give cu_number plus either one quarter (default latest) or a start-end range, and one credit union per call. It also routes the agent to the sibling needed for prerequisites ('Use find_credit_union to look up a cu_number') and rules out aggregation use cases, leaving nothing to inference.

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