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github_followers

Follower cards {id, login, type, url, avatar} — ~0.1/row; large accounts are expensive to page fully. Costs ~3 credits (0.1/result). Empty results and failures are never charged. Pass cache=true for a free 24h cache hit (default always fresh).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cacheNoSet true to serve from the 24h response cache (0 credits on hit). Default false — always fetch fresh.
limitNoMax items to return (default 30, max 100). Billed per result.
cursorNoOpaque cursor from a previous nextCursor (GitHub Link page=). Not a bare page number.
usernameYesGitHub username or profile URL, e.g. getify.

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 behavioral disclosure burden. It clearly discloses cost per result, approximate total cost, the 24h cache behavior, and that empty results and failures are never charged. It does not address auth or rate limits, but the cost and failure semantics are unusually explicit and valuable.

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?

Every sentence earns its place: result shape, pricing and pagination warning, and cache/failure billing. The description is compact, front-loaded with the core purpose, and contains no filler.

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?

Despite having no annotations and no output schema, the description gives the agent the essential return fields, cost expectations, pagination caution, and cache behavior. It could be slightly more explicit that the response is a list for the specified username, but combined with the schema it leaves few gaps.

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 all four parameters with 100% coverage, so the baseline is 3. The description adds useful pricing context for cache, limit, and paging, but it does not add new semantic meaning beyond what the schema already provides.

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 the resource as follower cards and lists the returned fields, making it clear this tool returns followers for a GitHub user. It lacks an explicit verb like 'list' or 'get', and it does not explicitly distinguish itself from github_following, but the resource and output shape are clear.

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 description implies usage context: pass a username, control cost with limit, and use cache=true for free repeated calls. It warns that large accounts are expensive to page fully, but it never explicitly says when to prefer this tool over alternatives like github_following or github_user, nor does it state exclusions.

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.