List responses for a survey with pagination and filters. Returns response metadata and answers.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number (default: 1) | |
| since | No | ISO date - only responses after this date | |
| until | No | ISO date - only responses before this date | |
| status | No | Filter by response status (default: completed) | |
| per_page | No | Results per page (default: 20, max: 50) | |
| survey_id | Yes | The survey ID |
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?
With annotations already declaring readOnlyHint=true and destructiveHint=false, the description adds value by stating 'Returns response metadata and answers,' which informs the agent about the output structure. It also mentions pagination and filters as behavioral traits. This goes beyond the annotations' safety implications.
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 sentence that front-loads the core purpose ('List responses for a survey') followed by additional useful details. No wasted words; every phrase earns its place.
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 tool's moderate complexity (6 params, 1 required) and lack of an output schema, the description provides enough context for selection: it states the resource, scope, pagination/filters, and return content. While not exhaustive on return format details, it is sufficient for a list operation with a well-defined schema.
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 schema provides 100% coverage with descriptions for all parameters, so the description does not need to compensate. The description's mention of 'pagination and filters' is a high-level summary that does not add detail beyond the schema. Baseline 3 applies.
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 ('List'), the resource ('responses'), and the scope ('for a survey'), clearly distinguishing it from sibling tools like get_response (single response) and list_surveys (surveys). It also mentions pagination and filters, which further clarifies the functionality.
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 this tool (to list responses with pagination and filters), and the context is clear given the sibling get_response for retrieving a single response. However, it does not explicitly state exclusions or alternatives, so it falls short of a 5.
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.
