List monitor events
monitors_events_listPull API for a monitor's events — queryable regardless of webhook delivery configuration.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| limit | No | ||
| cursor | No |
monitors_events_listPull API for a monitor's events — queryable regardless of webhook delivery configuration.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| limit | No | ||
| cursor | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, indicating a safe, read-only operation. The description adds value by stating that the tool is a 'pull API' and that it works irrespective of webhook delivery configuration, providing context about data availability that annotations do not cover. It does not contradict the annotations.
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 a single, concise sentence that front-loads the core purpose. It avoids unnecessary fluff and is easy to parse. It could be slightly more descriptive, but it is appropriately sized for a straightforward list endpoint.
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?
Given the lack of an output schema and 0% schema description coverage, the description is insufficient. It does not mention pagination behavior (despite 'limit' and 'cursor' parameters), the structure of the returned events, or any limitations. For a list tool with these parameters and no output schema, an agent would need more information to fully understand how to call it and interpret results.
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 0%, and the description does not explain any of the parameters (id, limit, cursor). It doesn't mention that 'id' refers to a specific monitor, or that 'limit' and 'cursor' control pagination. While the parameter names are self-explanatory to some degree, the description fails to compensate for the lack of schema details, leaving the agent uncertain about how to use them correctly.
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 tool pulls a monitor's events, which is a specific verb-resource combination. The phrase 'Pull API for a monitor's events' distinguishes it from sibling tools like monitors_list or monitors_get, and the title reinforces the intent. However, it doesn't explicitly mention that it lists events for a given monitor ID, relying on the required 'id' parameter to imply this.
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 provides one usage condition: the events are queryable regardless of webhook delivery configuration, which hints at when this tool is appropriate (e.g., when webhook setup isn't needed). However, it does not mention any alternative tools, such as monitors_checks_list, or explicitly state when not to use this tool. It gives a context but lacks clear guidance on tool selection compared to siblings.
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.