Register a webhook to receive notifications when survey events occur.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Webhook URL to receive POST requests | |
| events | No | Events to subscribe to (default: response.completed) | |
| secret | No | Secret for HMAC-SHA256 webhook signatures | |
| survey_id | No | Specific survey ID or '*' for all surveys |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a write operation (readOnlyHint=false), non-destructive (destructiveHint=false), and external interaction (openWorldHint=true). The description does not add significant behavioral detail beyond the purpose, such as validation or activation process, but it does not contradict 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 immediately states the verb and purpose. It contains no redundant information and is well-structured.
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 simplicity of a webhook creation tool, the description combined with comprehensive schema annotations covers the essential context. It does not mention return values, but that is acceptable without an output schema, and there are no obvious missing behavioral caveats.
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?
All parameters are fully described in the schema (100% coverage), so the description adds no parameter-specific meaning. The schema handles semantics adequately, making a baseline score of 3 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 uses a specific verb ('Register') with a clear resource ('a webhook') and purpose ('to receive notifications when survey events occur'). This clearly distinguishes it from sibling tools like update_webhook, delete_webhook, and list_webhooks.
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 when to use the tool (when creating a webhook to receive event notifications) but does not explicitly provide guidance on when not to use it or mention alternatives (e.g., updating an existing webhook with update_webhook).
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: surveys, responses, webhooks, analytics, and media library. Verbs like create, get, update, delete, list, and submit are applied clearly. No two tools have overlapping purposes.
All tools follow a consistent verb_noun pattern (e.g., create_survey, list_responses, update_webhook). Naming is uniform and predictable, with no mixed conventions or vague verbs.
15 tools is well-scoped for a survey platform, covering surveys, responses, webhooks, analytics, and media. Each tool serves a unique purpose, and the count is within the ideal 3-15 range, not feeling bloated or thin.
The tool surface covers full CRUD for surveys and webhooks, response submission and retrieval, analytics, and media listing. Minor gaps exist (no media upload, no response delete), but core workflows are complete and agents can achieve common tasks without dead ends.
