get_watchlistReturns a single watchlist by watchlistId with every member profile: profileId, handle, platform and follower count. Free to call. Use it to review or explain a list before searching it, or to pick profileIds for remove_watchlist_profiles. Cost: free.
| Name | Required | Description | Default |
|---|---|---|---|
| watchlistId | Yes | Watchlist id |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful behavioral context by stating the call is free and by specifying exactly what is returned: every member profile with profileId, handle, platform, and follower count. This goes beyond the annotation-only safety profile.
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 compact and front-loaded with the core return behavior. However, 'Free to call' and 'Cost: free' communicate the same fact twice, creating minor redundancy that keeps it from a perfect score.
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 single-parameter read tool with no output schema, the description is complete: it identifies the input, enumerates the output fields, states the cost, and connects the output to a likely follow-up mutation. An agent has enough information to invoke the tool correctly and interpret its result.
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% and the only parameter, watchlistId, is adequately described in the schema. The description merely references 'by watchlistId', adding no substantial meaning beyond the schema, so a baseline score of 3 is appropriate.
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 a specific verb ('Returns') and resource ('a single watchlist by watchlistId') and enumerates the returned fields. This distinguishes it from sibling tools like list_watchlists, which returns collections, and remove_watchlist_profiles, which mutates.
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 use cases: review or explain a list before searching it, and pick profileIds for remove_watchlist_profiles. It does not explicitly name alternative tools or state when not to use this tool, but the use-case guidance is concrete and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.