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

Annotations only declare readOnly/idempotent/openWorld, so the description carries real weight and does: it discloses the return contents (current conditions in Celsius, 3-hour steps for the next few hours, share-card link, website link), the MCP Apps card behavior, and the notable edge case that severe conditions are reported plainly without a joke. That edge-case disclosure is behavior an agent could not infer from annotations or schema.

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-loaded with the trigger, then returns, then exclusions — a sensible order. The attitude-level sentence largely duplicates the enum descriptions in the schema, which is the one place the text does not fully earn its space.

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?

With no output schema, the description must explain return values and does so concretely (units, forecast granularity, links, card rendering). Combined with the safety exclusions, an agent has everything needed to call it and set expectations correctly.

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 both parameters are already fully documented, including the city format and the enum meanings. The description restates the attitude levels but adds no syntax, defaulting, or format detail beyond the schema, so the 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?

States a specific verb and resource (looks up current temperature and conditions for a city and returns a joke) and clearly frames it as a novelty forecast, distinguishing it from any serious weather tool. The name-plus-description pair leaves no ambiguity about what the tool produces.

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?

Opens with an explicit trigger ("Use this when someone wants a funny or rude weather forecast") and closes with explicit exclusions ("Do not use it for serious weather needs such as safety decisions, severe-weather alerts... or multi-day forecasts"), each backed by a reason. This is the when/when-not pattern at full strength.

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