datasets_creators_search

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

With no annotations provided, the description takes on the full burden of disclosure. It transparently explains default exclusion of inactive accounts, the partial population of engagement metrics, and that creators without those metrics sort last and omit fields. This is thorough behavioral documentation beyond what the schema alone provides.

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 well-structured and concise. It starts with a clear purpose, then efficiently covers filtering, sorting, and data coverage. Every sentence adds essential information without redundancy. The length is appropriate for the complexity of the tool.

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 search tool with 11 parameters and no output schema, the description covers filtering behavior, sort options, and data coverage well. It explains that engagement metrics are missing for some creators. However, it does not describe the response format or pagination metadata, which would improve completeness.

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. The description adds significant context beyond the schema, such as the case-insensitive handle lookup, the coverage nuances for engagement_desc sort, and the default behavior for include_inactive. This extra information helps the agent understand parameter interactions and data quality.

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 it searches a TikTok creators dataset, specifying the indexed fields (follower counts, verified status, niche, engagement). However, it does not explicitly distinguish this tool from sibling tools like tiktok_search_user or tiktok_profile, which could cause confusion about when to use the dataset search vs live lookup.

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 provides some usage guidance: it explains that inactive accounts are excluded by default and how to include them, and it details the sort enum behavior and coverage nuances. However, it does not compare this tool to alternatives or state when to use it over other TikTok creator search tools, leaving the agent to infer from context.

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