game_maintenance

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

With no annotations, the description fully carries the behavioral disclosure burden. It explicitly notes single-GET behavior, no continuation-page auto-fetch, the local row/size limits, truncation reporting, and oversized-record refusal. It even discloses that filter effectiveness is not fully established, which is unusually honest and useful.

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?

The description packs in useful detail but is structurally messy, with run-on sentences and missing punctuation ('one logical GET request Does not auto-fetch'). It front-loads the purpose but then meanders into vague statements like 'Required inputs reflect tool policy as well as measured upstream requirements' which adds little. Dense but not polished.

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 two-optional-parameter read endpoint with no output schema and no annotations, the description covers the essential context: return contents, filtering caveats, pagination behavior, local limits, truncation notification, and error handling. Minor gaps like exact date formatting and the meaning of 'window_buffer_ms' prevent a perfect score.

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%, so the description must compensate. It does add that start_date/end_date are explicit date bounds that get forwarded, and mentions a tested September range that retained the same window, implying uncertain filtering. However, it does not explain expected date format, boundary inclusivity, or how the parameters affect the returned data, leaving the caller under-informed.

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?

The description opens with a specific verb and resource: 'Read scheduled maintenance windows and window_buffer_ms.' This clearly identifies the tool's operation and output. It also distinguishes itself from the many sibling endpoints by focusing on the maintenance domain, leaving no ambiguity about what resource it targets.

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?

No when-to-use or alternative-selection guidance is provided. The description does not state when a caller should choose this tool over any sibling, nor does it give context for typical use cases. The filtering caveat hints at behavior but not at usage context.

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