tiktok_profile_region_getGet the region code reported for a TikTok profile by handle.
| Name | Required | Description | Default |
|---|---|---|---|
| handle | Yes | TikTok handle to look up, with or without a leading @. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, covering the safety and open-endedness. The description adds minimal nuance with 'reported', implying the region may be user-reported, but it does not disclose behavior such as handling of missing or invalid profiles, return format, or potential null values. No contradiction with annotations.
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?
One concise sentence that front-loads the action and resource, with no redundant words or filler. Every element serves a purpose, making it optimally structured.
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 simple read-only operation with a single parameter, the description is sufficient for an agent to invoke the tool correctly. The absence of output schema means the response format is not specified, but for a single-value region code lookup, this is minor and does not hinder correct usage.
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?
The schema fully describes the single parameter 'handle' with details about accepting a leading '@'. The description merely references 'by handle' without adding any new semantic meaning, so it aligns with the baseline expectation when schema coverage is 100%.
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 action ('Get'), the specific resource ('region code'), and the scope ('TikTok profile by handle'). It unambiguously differentiates this tool from sibling profile tools like tiktok_profile_audience_get or tiktok_profile_get, which target other data aspects.
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 no guidance on when to use this tool versus alternatives. It does not mention that other profile-related tools exist for different data types (e.g., audience, engagement), nor does it offer any contextual cues for choosing region lookup over other profile attributes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool is clearly scoped to a specific platform and action (e.g., facebook_post_get vs instagram_post_get). Descriptions explicitly differentiate similar tools across platforms, and within-a-platform tools like tiktok_search_videos_list vs tiktok_search_hashtag_list have clear disambiguation notes.
All 167 tools follow a strict `platform_resource_action` pattern (e.g., youtube_video_comments_list). No mixing of styles—snake_case throughout, with consistent verb ordering (get, list, search, etc.).
The server has 167 tools, which is far beyond the typical well-scoped range of 3-15. While the broad multi-platform scope justifies many tools, this extreme number makes the tool surface overwhelming and difficult for an agent to navigate efficiently.
The tool set covers a wide range of platforms and operations including profile retrieval, post/video fetching, comments, search, transcripts, and ad library access. Minor gaps exist (e.g., no Facebook events or LinkedIn messaging), but the surface is comprehensive for a read-only data aggregation use case.