list_watchlistsReturns every watchlist on the account (both agent-created and web-app-created) with its watchlistId, name, notes, profile count and last-updated time. Free to call. Use it to recall an id for search_outliers, add_watchlist_profiles or get_watchlist. Cost: free.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnly, idempotent, and non-destructive behavior. The description adds useful context beyond annotations: output fields include watchlistId, name, notes, profile count, and last-updated time, and it notes the tool is free to call. No pagination or limits are disclosed, but the annotations significantly lower the burden.
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 front-loaded with the main return behavior and fields, which is good. However, 'Free to call.' and 'Cost: free.' are redundant statements of the same fact, so not every sentence earns its place.
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 zero-parameter, no-output-schema read-only list tool, the description is complete: it states what is returned, the fields included, the scope of watchlists, and how the result can be used. Nothing critical is missing for an agent to call it correctly.
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 and 100% schema description coverage, so there is no parameter meaning left unexplained. With no parameters, description-level parameter guidance is unnecessary; the baseline 4 applies.
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 states a specific verb and resource: 'Returns every watchlist on the account'. It also clarifies scope by including both agent-created and web-app-created watchlists, and it names the exact output fields. This clearly differentiates it from sibling tools that manage or analyze single watchlists.
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 explicitly says to use it 'to recall an id for search_outliers, add_watchlist_profiles or get_watchlist', giving concrete downstream use cases. It does not explicitly state when not to use the tool or contrast it with other listing tools like list_tracked_profiles, so it falls just short of a 5.
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.