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

Annotations already establish read-only, idempotent, non-destructive, closed-world access, so the description focuses on what the agent cannot get elsewhere: the exact returned fields (used, limit, remaining, plan, pool, resets_on), the Free-plan first-month note, and the extra per_client value when client_id is supplied. With no output schema present, this enumeration is exactly the behavioral disclosure an agent needs.

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 return fields, then adds the Free-plan caveat, then the client_id behavior, then the use case. The first sentence is long and parenthetical-heavy, and the usage guidance would be stronger placed earlier, but every clause carries information and none is 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-optional-parameter read tool with no output schema, the description covers return shape, plan-conditional behavior, per-client behavior, and intended questions. Only minor gaps remain, such as the date format of resets_on and what a 'pool' value looks like.

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 0% for the single optional client_id, but the description compensates by explaining its semantic effect: the response gains that workspace's own monthly limit under per_client. It does not explain defaults when client_id is omitted (implied) or what happens with an unknown id, so it adds real meaning but not a complete picture.

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 ('Returns') and a precise resource ('this month's Diagnostic allowance'), and the topic (quota/usage) is distinct from every sibling, which deal with scans, reports, or action items rather than allowance accounting. An agent can tell this apart from get_diagnostic and list_diagnostics without opening any schema.

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?

The closing sentence gives explicit use-case framing ('how many Diagnostics are left this month and when the allowance resets'), which maps cleanly onto user question phrasing. It stops short of naming an alternative tool or stating when not to call it, so it is clear context without exclusions.

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