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tiktok_comments

TikTok comments — clean schema plus authorName, stable authorId/authorSecUid and commentLanguage for listening loops. Unresolvable videos are 404 at 0 credits. Costs 2 credits. Empty results and failures are never charged. Pass cache=true for a free 24h cache hit (default always fresh).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic TikTok video URL, e.g. https://www.tiktok.com/@khaby.lame/video/7646812028874673439. Not a YouTube/Instagram/Facebook 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 24h response cache (0 credits on hit). Default false — always fetch fresh.
limitNoMax items to return (default 50, max 500). Flat 2 credits per call.
cursorNoPagination cursor. Leave empty for the first page; then pass the nextCursor value returned in the previous response (a numeric offset, e.g. 50). A null nextCursor means the end of the comments.

TDQS

A3.8/5.0
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 substantial work: it discloses the 2-credit cost, the 404-at-0-credits edge case for unresolvable videos, no-charge on empty/failed results, and the free 24h cache hit with default-fresh behavior. It stops short of covering auth needs or rate limits, but the pricing, failure, and caching semantics are unusually explicit for a description.

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

Conciseness5/5

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

Four short sentences front-load the core purpose and pack in output-shape, pricing, failure, and caching semantics without filler. There is minor pricing redundancy ('Costs 2 credits', 'never charged', 'free 24h cache hit'), but each mention adds a distinct nuance, so every clause earns its place.

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 4-parameter tool with no annotations and no output schema, the description covers pricing, failure modes, caching behavior, and key response fields, while leaving pagination mechanics to the well-documented schema. It is missing only minor context such as rate limits and authentication expectations, which are likely shared across the account-level sibling tools.

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 documents url (with cross-platform warnings), cache, limit, and cursor/nextCursor pagination. The description adds only marginal value by tying cache=true to the free 24h cache hit, which mostly restates what the schema's cache parameter already explains.

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 states the resource ('TikTok comments') and hints at the output shape (authorName, stable authorId/authorSecUid, commentLanguage), making the tool's function unambiguous. It lacks an explicit verb like 'fetch' or 'list' and never names sibling tools such as tiktok_comment_replies, so sibling differentiation relies on inference from the platform and field details rather than explicit 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?

The phrase 'for listening loops' implies a use case (tracking commenters over time via stable author IDs), and the cache/cost notes signal when the cheap path applies. However, there is no explicit when-to-use guidance, no exclusions, and no mention of alternatives like tiktok_comment_replies or youtube_comments, so an agent must infer when this tool is preferred over siblings.

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.