get_trending_outliersReturns the current top trending outlier posts across TikTok, Instagram and YouTube, deduplicated to one per creator. Free and unauthenticated (rate-limited per IP; cached ~2 hours). A taste of the database. For filtered search, transcripts and on-demand crawling, create an API key. Cost: free.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, and non-destructive. Description adds rate-limit per IP, ~2h caching, and deduplication behavior, providing useful operational context beyond 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?
Description is mostly concise and front-loaded with the main purpose. Minor redundancy: 'Free' appears twice (in sentence 2 and 'Cost: free'), and 'A taste of the database' is somewhat vague but adds qualitative context.
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 no parameters and no output schema, the description covers the tool's functionality, platform scope, deduplication, caching, rate limits, and authentication model, plus pointers to more advanced features. This is sufficiently complete for a simple read-only tool.
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 tool has zero parameters, so schema coverage is trivially 100%. Baseline for 0 params is 4; description adds context about the returned data but nothing parameter-related is needed.
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?
Description clearly states it returns current top trending outlier posts across TikTok, Instagram, and YouTube, deduplicated per creator. This specific verb+resource scope distinguishes it from sibling tools like search_outliers and niche_trends.
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?
Explicitly notes it is free and unauthenticated, contrasting with filtered search, transcripts, and on-demand crawling which require an API key, implying alternative tools for those use cases. However, it doesn't name specific sibling tools, leaving some ambiguity.
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.
Most tools have clearly distinct purposes (search, profile management, post retrieval, async jobs, billing). Some overlap exists among get_trending_outliers, niche_trends, and search_outliers, but their descriptions differentiate free/unauthenticated, niche-specific, and filtered search, so an agent can usually pick correctly.
The vast majority of tool names follow a verb_noun pattern (crawl_profile, get_post, remix_post, track_profile). The main exception is 'niche_trends', which is a noun phrase, and the minor spelling of 'topup' instead of 'top_up'. Otherwise, naming is consistent enough to predict tool behavior.
At 21 tools, this is slightly above the typical 3-15 range, but the broad scope (search, crawling, tracking, media handling, transcripts, remixing, billing) justifies the number. Each tool serves a distinct function, and none feel redundant, so the count is reasonable for the domain.
The tool set covers the core workflow well: searching outliers, crawling/tracking profiles, fetching posts/media/transcripts, and generating remixes. However, there is no way to list all posts for a specific profile (only 'recent tracked posts' via get_profile and an incremental feed via get_tracked_updates), which is a notable gap for deep creator analysis.