get_bucket
Fetch one webhook endpoint by id, including its url and inbox_url.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| bucket_id | Yes | The endpoint id. |
Fetch one webhook endpoint by id, including its url and inbox_url.
| Name | Required | Description | Default |
|---|---|---|---|
| bucket_id | Yes | The endpoint id. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description must convey behavior. 'Fetch' implies a read-only operation, but it does not explicitly state that it has no side effects, nor does it mention authentication requirements, error behavior (e.g., 404 on missing id), or response format beyond the two mentioned fields. This is adequate but lacks depth.
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, front-loaded sentence that states the action, resource, scope, and key return fields without any redundant wording. Every word contributes to understanding the tool.
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, single-parameter fetch tool with no output schema, the description adequately covers the core purpose and partially describes the return value (url and inbox_url). It does not detail error cases or authorization, but these are less critical for a straightforward get operation, making this sufficiently complete.
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 input schema provides 100% coverage of the single parameter (bucket_id) with a description ('The endpoint id.'), so the schema already explains the meaning. The description's mention of 'by id' adds no additional semantic information beyond what the schema provides, thus yielding the baseline score.
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?
Description uses the specific verb 'Fetch' and clearly identifies the resource ('one webhook endpoint') and the access pattern ('by id'), while also mentioning the return fields (url, inbox_url). This clearly distinguishes it from sibling tools like list_buckets (all buckets) and delete_bucket (delete).
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 usage context is implied by the 'by id' phrasing, suggesting this tool is for retrieving a single bucket when the id is known, rather than listing all buckets. However, it does not explicitly mention alternatives or exclusions, such as 'use list_buckets to list all endpoints', leaving the guidance implicit.
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 targets a distinct resource and action: buckets, events, schemas, deliveries, forwarding, verification, replay, and waiting. Even similar pairs like latest_event vs list_events are clearly differentiated by purpose, with no overlapping responsibilities.
Most tools follow a consistent verb_noun pattern with underscores, such as create_bucket, list_events, and delete_bucket. The only slight deviation is 'latest_event', which uses an adjective instead of a verb, but it remains intuitive and does not disrupt the overall predictability.
At 17 tools, the set is slightly above the typical well-scoped range of 3-15, but the domain covers buckets, events, schemas, deliveries, configuration, and more, so each tool serves a distinct and justified purpose. The count feels appropriate for the platform's breadth rather than excessive.
The set covers the primary lifecycle for buckets, events, and schemas, including create, read, list, and delete operations. However, there is no way to update or delete a forwarding rule after creation, and no explicit update operation for bucket metadata, leaving notable gaps in managing configurations.