facebook_post_comments_replies_listList replies to a Facebook comment. Accepts a from post comments. Returns a list (use cursor when paginated).
| Name | Required | Description | Default |
|---|---|---|---|
| cursor | Yes | Comment `repliesCursor` from post comments, or `page.nextCursor` to paginate replies. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description doesn't need to restate safety. It adds a pagination note: 'Returns a list (use cursor when paginated).' This is useful behavioral context beyond the schema. However, it omits any mention of error handling, rate limits, or the structure of the returned list, and the incomplete sentence about the cursor reduces clarity.
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 short but contains a broken, incomplete sentence: 'Accepts a from post comments.' This is not just concise; it's ungrammatical and confusing. The structure is not front-loaded effectively, as the key action is stated first but followed by a garbled clause. Wasteful and error-prone.
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?
With no output schema, the description provides minimal return info ('Returns a list') and pagination guidance. It does not explain what fields or structure the replied list contains, but for a simple one-parameter list tool this might be adequate. However, given the ambiguity of the 'Accept a' phrase, an agent might be unsure of the exact input format despite the schema. Overall, it meets the minimum but has room for improvement.
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?
The schema fully documents the only parameter (cursor) with a precise description of where it comes from and how to paginate. The description's phrase 'Accepts a from post comments' adds no value and is actually less clear than the schema. Since schema coverage is 100%, the baseline is 3, and the description does not enhance it.
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 and resource clearly: 'List replies to a Facebook comment.' It distinguishes from sibling facebook_post_comments_list by focusing on replies. However, the phrase 'Accepts a from post comments' is incomplete and vaguely worded, which slightly reduces clarity.
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 explicit guidance on when to use this tool versus alternatives like facebook_post_comments_list. The description hints that it takes a cursor from post comments, implying a prerequisite, but does not explicitly state the workflow or contrast with other comment-listing tools. The agent is left 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.