webhookEndpoints_deliveries_listList delivery attempts for a webhook endpoint. Supports limit, opaque cursor continuation, and optional after (ISO timestamp) to enter oldest-first tail mode for listeners.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| after | No | ||
| limit | No | ||
| cursor | No | ||
| status | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint=true, and the description adds behavioral detail: it explains the opaque cursor continuation and the 'after' parameter for oldest-first tail mode, which is useful for pagination behavior. It doesn't contradict annotations; it adds context beyond 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?
The description is a single, efficient sentence that front-loads the main action and packs in key feature details without fluff. Every word earns its place, and the structure is clear.
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 5-parameter tool with no output schema and 0% schema coverage, the description covers the core pagination and ordering behavior but omits the status filter and any response format hints. It's adequate for basic use but incomplete for full parameter understanding, given the schema provides no descriptions.
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?
With 0% schema description coverage, the description must explain parameters. It covers `limit`, `cursor`, and `after` (with non-obvious 'oldest-first' semantic), but omits `id` (obvious from title) and `status` (a filter with enum). It partially compensates for the schema gap but not fully, missing the status filter.
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 verb 'List' and the resource 'delivery attempts for a webhook endpoint'. It distinguishes itself from sibling tools like webhookEndpoints_list (which lists endpoints) and webhookDeliveries_redeliver, making the purpose unambiguous.
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 clear context: it lists delivery attempts for a webhook endpoint, and adds pagination/ordering details. While it doesn't explicitly exclude alternatives, the context is sufficient for an agent to know when to use it. It lacks explicit 'use instead of X' but the purpose is clear.
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.