update_webhook
Update an existing webhook's configuration.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| fields | Yes | Fields to update,required | |
| api_key | No | MailerCloud API key | |
| webhook_id | Yes | Webhook ID,required |
Update an existing webhook's configuration.
| Name | Required | Description | Default |
|---|---|---|---|
| fields | Yes | Fields to update,required | |
| api_key | No | MailerCloud API key | |
| webhook_id | Yes | Webhook ID,required |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly=false, idempotent=true, destructive=false, so the description is not burdened with that. But the description adds no additional behavior: it doesn't say whether the update replaces the whole configuration or merges only provided fields, nor does it mention authentication requirements or side effects. It merely restates the operation.
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 without filler. It loses some value from being overly terse, but as a concise statement it is acceptable.
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 tool that accepts a free-form 'fields' object and returns no documented output, the description is incomplete. An agent is not told what webhook settings can be updated, whether the operation is a PATCH-like partial update, or what the result will look like. The sibling operations and annotations don't fill these gaps.
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 describes all three parameters (webhook_id, fields, api_key) with brief descriptions, and schema coverage is 100%. The tool description itself says nothing about parameters, so it doesn't add meaning beyond the schema. The nested 'fields' object remains unconstrained, but the description offers no hints about valid keys.
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 a specific verb ('Update') and resource ('existing webhook's configuration'), which distinguishes it from create, delete, toggle, and get webhook siblings. However, it does not articulate exactly what aspects of configuration can be changed, leaving some ambiguity relative to toggle_webhook which might also change configuration (e.g., enabling).
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 guidance is provided on when to use update_webhook versus create_webhook, toggle_webhook, or delete_webhook. The description neither states prerequisites nor defines scenarios, so an agent must infer the tool's role purely from its name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Tool purposes are largely distinct, with clear separation between CRUD operations, analytics, and deliverability tools. Some overlap exists between get_campaign, analyze_campaign, and campaign_health_dashboard, but descriptions clarify scope sufficiently.
Most tools follow a consistent verb_noun pattern (list_, get_, create_, update_, delete_, send_). Minor exceptions like campaign_health_dashboard and engagement_funnel are descriptive but break the pattern.
With 47 tools, this is a very large surface area. While the variety reflects the breadth of email marketing operations, the count exceeds what is typically manageable and suggests potential redundancy or over-scoping.
The tool set covers most core workflows: contact/list management, campaign lifecycle, templates, webhooks, analytics, and transactional email. Minor gaps like no delete for templates or tags are acceptable but not fatal.