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Create a Watchlist

create_watchlist

Creates an empty watchlist (a named set of creators) and returns its watchlistId. Fill it with add_watchlist_profiles, then pass the id to search_outliers as watchlistId to scope any search to exactly those accounts. Watchlists created here appear in the owner's web app too. Free to call. Watchlists count against a workspace allowance that comes from a subscription or is earned from API spend (every API key holder starts with 1); an over-limit call explains what unlocks more. Cost: free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesDisplay name, 1-80 characters
notesNoOptional notes, up to 500 characters

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the annotations, the description reveals important non-obvious behavior: watchlists appear in the owner's web app, the call is free, and watchlists count against a workspace allowance. It also explains the over-limit behavior. This is rich contextual detail that helps an agent anticipate side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose and return value. It includes a minor redundancy between 'Free to call' and 'Cost: free', but overall every sentence contributes useful workflow, allowance, or behavior information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity, the description covers creation, return value, downstream integration with two sibling tools, web-app visibility, and quota implications. There is no output schema, but the key return value (watchlistId) is stated. The description is sufficient for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already documents both parameters completely (name and notes) with descriptions, so schema coverage is 100%. The description does not add much parameter-level detail, but it doesn't need to because the schema carries the load.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that this tool creates an empty watchlist, a named set of creators, and returns a watchlistId. It is easily distinguished from siblings like add_watchlist_profiles, delete_watchlist, and list_watchlists by focusing on the creation action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives an explicit usage workflow: create the watchlist, populate it with add_watchlist_profiles, and then pass the id to search_outliers. It does not explicitly mention when not to use it versus alternatives, but the workflow context is clear and practical.

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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TDQS

A3.9/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count4/5

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.

Completeness3/5

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.

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