tiktok validate query

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds useful behavioral context about the validation logic (dimension grouping, lifetime compatibility) and that it is a pre-execution step. This goes beyond annotations without contradicting them.

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 a tight two-sentence structure with the primary purpose front-loaded. Every sentence adds distinct value with no redundancy or 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?

With an output schema present, return values need not be explained. The description covers purpose, timing, and validation scope, which is sufficient for an agent to decide when to call it. It does not detail failure behavior or prerequisites, but these are likely covered by the output schema and annotations.

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 all five parameters are documented in the schema. The description does not add parameter-specific semantics beyond what the schema provides; it only references the metric/dimension combination generically. This meets the baseline for high coverage.

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 the tool's purpose: validating a TikTok metric/dimension combination before executing. It specifies what is checked (dimension grouping rules, lifetime compatibility, metric/dimension compatibility), which distinguishes it from all sibling tools that fetch data rather than validate.

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 indicates usage context with 'BEFORE executing', implying it should be used prior to query tools like tiktok_get_insights or tiktok_get_report_raw. However, it does not explicitly name alternatives or provide when-not-to-use guidance, leaving some inference to the agent.

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