facebook_group_getGet a Facebook group by URL or group id.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Public Facebook group URL. | |
| groupId | No | Numeric Facebook group id when you have it instead of a full URL. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds no behavioral context, such as what happens when both url and groupId are provided, whether the group must be public, or any rate-limit/auth requirements. Since annotations carry the burden, a 3 is appropriate — the description doesn't contradict them, but it doesn't enrich the behavioral picture.
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?
A single sentence with no wasted words. The core purpose and identification methods are front-loaded, and everything present serves a function. Perfectly concise.
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 read-only get tool, the description is functionally sufficient: it states what and how. However, it lacks any indication of return format or extra context (e.g., does it return member count, description, etc.), though no output schema exists. Given the tool's simplicity and the safety annotations, this is adequate but not rich.
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% — the schema already documents each parameter's purpose (URL vs numeric id) and constraints. The description's 'by URL or group id' essentially restates this, adding no new meaning beyond the schema. Baseline 3 is correct when the schema does the heavy lifting.
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 clearly states the action ('Get'), the resource ('a Facebook group'), and the two identification methods ('by URL or group id'). It distinguishes from siblings like facebook_group_posts_list by focusing on the group itself rather than its posts, though it doesn't explicitly name the sibling for contrast.
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?
No guidance on when to use this tool vs alternatives. There is no mention of 'use this to retrieve group metadata' or 'if you need posts, use facebook_group_posts_list'. The sibling list includes relevant alternatives, but the description does not point to them, leaving the agent to infer usage context.
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.