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

Annotations already declare readOnly/idempotent/non-destructive, so safety is covered. The description adds what the annotations cannot: the output is descriptive rather than predictive, and results degrade to directional signals below the three-month threshold — meaningful context for interpreting weak results.

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 compact sentences: output shape first, then the descriptive-not-predictive framing, then the data requirement. Nothing is repeated and the most important caveat is front-loaded before the agent commits to a narrow date range.

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 an output schema present, return values need no explanation, and the schema already handles parameter details. What remains — data-sufficiency threshold, caution about volatility with few points, and the non-forecast framing — is covered, leaving only minor gaps such as behavior when the range falls entirely outside available data.

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% with per-parameter descriptions, patterns, bounds and the enum format default documented inline. The description mentions 'range' and 'monthly' but adds no syntax, defaults or coupling rules (e.g. from vs months interaction) 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?

States a specific verb and resource ('fit a trend to each Pokémon's monthly usage across a range') and a concrete output ordering (fastest rising, fastest declining, most volatile). This is clearly an aggregate ranking tool, distinct from per-Pokémon trend tools, though no sibling is named explicitly.

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 real precondition ('needs at least three months of history in the range') and interpretive guidance for thin data. It does not say when to prefer this over get_usage_trend, get_top_usage or get_meta_shifts, so routing between the trend tools is still left to inference.

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