facebook_events_listList Facebook events for a city by explore URL. Returns a list (use cursor when paginated).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public Facebook Events explore URL for a city. | |
| time | No | Optional time window for events. | |
| cursor | No | Opaque pagination cursor returned by a previous response. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the description carries a lighter burden. The description adds the key behavioral detail of pagination ('use cursor when paginated') and confirms the return type is a list. This goes beyond the annotations without contradicting them.
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?
Two sentences with zero fluff: the first states the core operation and input, the second covers the return type and pagination. The information is front-loaded and every word earns its place.
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 moderately simple list tool with three params, an existing output schema is absent, and annotations cover safety, the description is nearly complete. It tells the agent what it returns and how to paginate, which is the critical runtime behavior. Minor gaps remain, such as error behaviors or what the list items contain, but these are not essential for calling the tool correctly.
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%, and each parameter (url, time, cursor) is already documented in the schema. The description only briefly alludes to 'explore URL' and 'cursor' without adding deeper semantics or examples, so it adds no value beyond what the schema already provides. Baseline 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 clearly states the action ('List'), the resource ('Facebook events for a city'), and the method ('by explore URL'). This distinguishes it from siblings like facebook_events_search_list (which likely does a keyword search) and facebook_event_get (singular event), though it doesn't explicitly name alternatives. The purpose is unambiguous and specific.
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 implies this tool is for when you have a city's explore URL, but it gives no explicit guidance on when to prefer this over comparable siblings like facebook_events_search_list or facebook_profile_events_list. No exclusions or alternative conditions are provided, leaving the selection largely to inference.
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.