github_profile_following_listList accounts a GitHub profile follows. Accepts a username. Returns a list (use cursor when paginated).
| Name | Required | Description | Default |
|---|---|---|---|
| cursor | No | Pagination cursor from a previous response (numeric page index as a string). | |
| handle | Yes | GitHub username whose following list should be listed. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description adds that the tool 'Returns a list' and advises 'use cursor when paginated', which provides some behavioral context about the return type and pagination. However, it does not disclose the structure of list items (e.g., usernames, profile objects) or how to detect further pages beyond the cursor parameter. This provides moderate value beyond the annotations but is not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences with zero fluff. The core purpose is front-loaded, followed by input and return/pagination hints. Every sentence earns its place, making it highly efficient and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters and readOnly annotations, the description is mostly adequate but leaves a notable gap: the exact composition of the returned list. Since there is no output schema, the agent is left wondering whether the list contains usernames, full profile objects, or something else. The pagination hint is useful, but the missing return format detail reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%; both handle and cursor have clear descriptions. The description adds little beyond that: 'Accepts a username' restates the handle parameter, and 'use cursor when paginated' echoes the cursor's schema description. Since the schema already carries the full semantic weight, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'List' with a specific resource 'accounts a GitHub profile follows', which clearly distinguishes it from the sibling tool github_profile_followers_list. The clause 'Accepts a username' further specifies the input, and the title reinforces the action. This is unambiguous and unique among many similar profile-related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly explain when to use this tool versus alternatives like github_profile_followers_list or github_profile_get. It only states the function without any context on selection criteria, prerequisites, or exclusions. The agent must infer usage from the name and title, which is not sufficient guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool is clearly scoped to a specific platform and action (e.g., facebook_post_get vs instagram_post_get). Descriptions explicitly differentiate similar tools across platforms, and within-a-platform tools like tiktok_search_videos_list vs tiktok_search_hashtag_list have clear disambiguation notes.
All 167 tools follow a strict `platform_resource_action` pattern (e.g., youtube_video_comments_list). No mixing of styles—snake_case throughout, with consistent verb ordering (get, list, search, etc.).
The server has 167 tools, which is far beyond the typical well-scoped range of 3-15. While the broad multi-platform scope justifies many tools, this extreme number makes the tool surface overwhelming and difficult for an agent to navigate efficiently.
The tool set covers a wide range of platforms and operations including profile retrieval, post/video fetching, comments, search, transcripts, and ad library access. Minor gaps exist (e.g., no Facebook events or LinkedIn messaging), but the surface is comprehensive for a read-only data aggregation use case.