get_top_trends

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

Annotations already mark the tool as read-only, open-world, and idempotent, and the description adds substantial behavioral context beyond that: it is a live board rather than a keyword lookup, category omission mixes boards, rank_change compares to a prior snapshot, and rate-limit/quota exhaustion should be reported to the user. No contradiction with annotations exists.

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 is dense and front-loaded with the core constraint, and every sentence carries an instruction or exclusion. It repeats some schema-level details such as window values and defaults, making it slightly longer than strictly necessary, but there is no fluff.

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 a full input schema, an output schema, and a description covering purpose, category requirements, sort semantics, sibling routing, and quota/rate-limit behavior, the agent has everything needed to invoke the tool correctly. No critical operational context 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 the baseline is 3, but the description adds real decision logic on top: when to pass category, what sort values mean, and how window relates to rank_change. It partially repeats schema details, but it clarifies the intended usage patterns rather than just naming parameters.

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 clearly states that the tool returns a live top-trending board for exactly one feed type and explicitly says there is no keyword. It distinguishes itself from siblings by specifying that app history should be handled by get_growth or get_time_series, making the tool's niche unambiguous.

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 description gives explicit when-to-use and when-not-to-use guidance: pass category for four named feed types, use sort='rank_change' for climbers, avoid get_time_series for live boards, and route app-history requests to alternatives. It even includes rate-limit handling instructions for the user-facing response.

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