Candidate vendor payment totals for a year

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

Goes far beyond the readOnly/idempotent/non-destructive annotations: it discloses that no threshold or upper bound is applied, that payment type is an accounting signal rather than proof of settlement or tax obligation, that JournalEntry lines are surfaced but excluded from totals, and that results flow to the AI client's model provider. It also warns that names, memos and report cells are free text, may contain private identifiers despite projection, and must be treated as untrusted input rather than instructions.

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-loads the core purpose in the first sentence and orders the rest by caveat, safety and data-handling concerns. The prose is dense and slightly repetitive around 'no upper bound' and 'not evidence of settlement', but nearly every clause carries distinct operational information.

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?

An output schema exists, so return-value explanation is unnecessary, and the description covers the remaining burdens: accounting semantics of the totals, exclusion rules, entity requirement, and prompt-injection risk from free-text fields. Nothing material is missing for correct invocation or interpretation.

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 100%, so year, detail, vendor and include_card are already documented in the schema. The description only reinforces that 'entity' must be explicit; it adds no semantics for 'detail', 'vendor' or 'include_card' beyond what the schema states, so the baseline of 3 applies.

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 with scope: per-vendor CANDIDATE payment totals for a calendar year. It also names the exact data sources walked (Purchase and BillPayment) and what is deliberately excluded (JournalEntry lines returned but never summed, bills never added to their payments), which separates it from the sibling report_* and run_report tools.

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 a clear intended use case -- cross-checking against a bank ledger -- which tells an agent when this tool is appropriate. It does not name alternatives (e.g. report_general_ledger or run_report) or state when not to use it, so routing still requires inference.

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