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

With no annotations, the description carries the burden and does most of it: it discloses the auth requirement (x-api-key or Bearer), the data source (usage events logged via record_usage, so empty until that runs), and the org scoping constraint that org_id must match the key's org. It does not mention pagination, rate limits, or behavior on an empty window, which keeps it from 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?

Three sentences with zero filler, front-loaded with what is returned before the usage guidance and then the auth prerequisite. Every sentence carries distinct information an agent needs.

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, but the description enumerates the return content (total cost, request count, per-model and per-provider breakdowns), and prerequisites are covered. For a two-optional-parameter read tool, nothing an agent needs 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%, so both parameters are already documented with defaults, bounds, and org scoping. The description restates the org_id default/must-match rule but adds no format or syntax detail beyond the schema, so baseline 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?

Specific verb+resource ('Get a summary of actual recorded LLM spend') plus the exact contents (total cost, request count, breakdowns by model and provider). It explicitly distinguishes itself from estimate_cost by naming the contrast case (hypothetical cost estimate) and identifies record_usage as the data source.

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 trigger condition directly: 'Use when the user asks what they've actually spent, as opposed to a hypothetical cost estimate.' That is an explicit when-to-use plus an explicit alternative, so an agent can route between get_usage_summary and estimate_cost/compare_costs without opening either schema.

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