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soundcloud_track

SoundCloud track — plays/likes/license, tags[], nested artist{}, streamUrl when streamable (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
urlYesSoundCloud track URL. 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 response cache (default TTL). Default false — always fetch fresh. Prefer cacheMaxAge when you need 1d–30d freshness control.
cacheMaxAgeNoMax age of a cached response: 1d, 3d, 7d, 14d, or 30d. When set, enables caching with that TTL.

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden, and it delivers: it discloses the 1-credit cost, that empty results and failures are never charged, and the cache semantics (default fresh, cache=true gives a free 24h hit). The conditional 'streamUrl when streamable' also tells the agent the output is shape-dependent. It stops short of covering rate limits or auth, but billing and caching are the most decision-relevant traits.

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?

Two compact sentences that front-load the data fields, then cover billing and caching. The payload shorthand (plays/likes/license, tags[], nested artist{}) is efficient. Minor redundancy: '(1 credit)' is immediately restated as '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?

For a single-resource fetch tool with three fully documented parameters and no output schema, the description covers the essentials: what data comes back, cost, failure charging, and cache control. It is complete enough for an agent to call it correctly. The absence of error-format or rate-limit detail is a minor gap given the billing and cache coverage.

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%, so the baseline is 3. The schema already thoroughly documents url (including the cross-platform prohibition), cache, and cacheMaxAge TTL values. The description adds only the 24h specificity for cache=true and the fact that the hit is free, which is marginal value over the schema.

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 identifies a specific resource (SoundCloud track) and enumerates the returned payload: plays/likes/license, tags[], nested artist{}, and conditional streamUrl. This makes the tool's scope clear and distinguishes it from siblings like soundcloud_artist and soundcloud_artist_tracks, though it never explicitly names those alternatives.

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

Usage Guidelines2/5

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

No guidance on when to choose this tool over alternatives. It does not say 'use this for track-level data, use soundcloud_artist for artist profiles' or contrast with spotify_track. The cache and billing notes describe how to invoke, but the description provides no tool-selection context in a large sibling list.

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.