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spotify_artist

Spotify artist — followers, monthlyListeners, worldRank, topCities, topTracks with playCount, concerts, and related artists (1 credit). Costs 1 credit. Empty results and failures are never charged. Pass cache=true for a free 24h cache hit (default always fresh).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rawNoInclude the upstream GraphQL payload as data.raw. Default false — omit unless you need fields not in the normalized shape (~80% of the old response body).
urlYesSpotify URL, URI, or ID. The URL platform must match this endpoint's platform. Do not pass cross-platform URLs, e.g. YouTube to TikTok, Instagram to Facebook, LinkedIn to X/Twitter, or Pinterest to Rumble.
cacheNoSet true to serve from the 24h response cache (0 credits on hit). Default false — always fetch fresh.

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden and does real work: it discloses the 1-credit cost, guarantees that empty results and failures are never charged, and explains the cache-strue free 24h hit with a default of always fresh. These are exactly the operational behaviors an agent needs to decide whether to call the tool, though it does not cover error-shape or upstream-unavailable behavior.

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 front-loaded with the field list and stays compact at roughly 60 words, with the cache guidance earning its place. The main flaw is redundancy: the 1-credit cost is stated twice, once parenthetically '(1 credit)' and once as its own sentence 'Costs 1 credit.'

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

Completeness4/5

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

Although no output schema exists, the description enumerates the expected return fields, giving the agent a concrete picture of the result shape. Given the low complexity (3 params, 1 required) and complete 100% schema coverage plus the disclosed cost/cache/failure policies, little is missing — only field types and error-response structure go unspecified.

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?

Schema description coverage is 100% and the schema itself is detailed: raw explains its purpose and when to omit it, url explains accepted formats plus the cross-platform warning, and cache covers defaults and costing. The description only restates the cache behavior ('free 24h cache hit'), adding no new parameter meaning, so the baseline 3 for full-coverage schemas applies.

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

Purpose4/5

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

The description names the exact resource ('Spotify artist') and enumerates the concrete fields returned: followers, monthlyListeners, worldRank, topCities, topTracks with playCount, concerts, and related artists. This differentiates it from the Spotify siblings (spotify_track, spotify_album, spotify_podcast) at a glance, but the verb is implicit — it never states 'get' or 'fetch' — so it stops just short of a fully explicit purpose statement.

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

Usage Guidelines3/5

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

Usage context is implied by the resource type and field list: an agent needing monthlyListeners or worldRank for a Spotify artist would naturally route here. However, no explicit 'use when' condition, exclusion, or alternative is named, so the agent gets no help deciding between this and spotify_track, spotify_album, or the platform-mislatched URL cases beyond what the schema's url parameter warns about.

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

B3.2/5.0
Disambiguation3/5

The platform-prefix convention keeps most of the 178 tools clearly separated, but several clusters are genuinely ambiguous: tiktok_live_info is explicitly described as 'Identical to TikTok Live', instagram_basic_profile and instagram_channel_details both return profile stats, and facebook_profile_posts overlaps with facebook_profile_reels. The generic 'Summarizer' descriptions for facebook_summarize, instagram_summarize, and tiktok_summarize provide no disambiguating detail at all.

Naming Consistency4/5

The dominant snake_case platform_resource_suffix pattern is followed remarkably consistently across 178 tools (e.g. youtube_channel_videos, tiktok_search_users, reddit_subreddit_posts). Minor deviations exist: the same creator resource is called 'channel' in some tools (tiktok_channel_details, instagram_channel_posts) but 'profile' or 'user' in others (facebook_profile_posts, twitch_user_videos, linnkme_profile); link-in-bio tools mostly use _page but linkme uses _profile; and the video_summarize/video_transcript pair lacks a platform prefix.

Tool Count2/5

At 178 tools this is far beyond what any agent can efficiently navigate in a single flat namespace, and even individual platform subsets exceed reasonable bounds (TikTok alone has ~34 tools, YouTube ~25). The sheer breadth of the multi-platform scope partially justifies the count, but the server would be far more usable split into per-platform servers.

Completeness4/5

The read-only data surface is impressively thorough: nearly every platform has profile + content + search + comments coverage, and TikTok, YouTube, Instagram, and Facebook are covered end-to-end including shops, ads, transcripts, and summaries. Notable gaps are minor: Twitter has no keyword search tool, LinkedIn lacks comments, and Reddit has no user-profile endpoint, but none of these create dead ends for the server's core data-retrieval purpose.