List all surveys in your PollBolt account with pagination.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number (default: 1) | |
| status | No | Filter by status | |
| per_page | No | Results per page (default: 20, max: 100) |
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 declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds the key behavioral trait of pagination, which is useful context. It does not mention filtering, but that is documented in the schema, so the added value beyond annotations is adequate.
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 with zero wasted words. It conveys the core purpose and pagination in a compact form, earning the highest score for conciseness.
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 list tool with good annotations and fully documented parameters, the description covers the essential purpose and pagination. The lack of an output schema is mitigated by the tool's simplicity, though mentioning status filtering could have made it marginally more 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?
Schema description coverage is 100%, with all three parameters (page, status, per_page) having clear descriptions. The tool description does not add extra parameter semantics beyond what the schema provides, so the baseline of 3 is 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 clearly states a specific verb ('List') and resource ('surveys'), distinguishing it from sibling tools like list_responses and get_survey. The phrase 'in your PollBolt account' adds scope, 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 implies usage (listing surveys) but does not explicitly state when to use this tool versus alternatives like get_survey or list_responses. There are no exclusions or conditional guidance, so it remains at an implied-usage level.
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.
