List surveys
list_surveysSurveys in the active workspace (newest first, max 300) with status (draft/live/paused/closed), target quota, completes, CPI, total and country.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
list_surveysSurveys in the active workspace (newest first, max 300) with status (draft/live/paused/closed), target quota, completes, CPI, total and country.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds behavioral details beyond annotations: the result is ordered newest first, capped at 300, and includes specific fields. This provides useful context about the operation's behavior, aligning with annotations with no contradiction.
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?
A single, tightly worded sentence that front-loads the resource (surveys) and workspace scoping, then lists key attributes. No filler, every word contributes. Excellent structure.
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?
With no output schema and no parameters, the description must explain what is returned. It lists the fields, ordering, and a maximum count, which is sufficient for a zero-parameter listing tool. It doesn't mention pagination beyond the max, but that is a minor gap. Overall adequate for an agent to call correctly.
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?
There are zero parameters, so the description carries no burden for parameter documentation. The baseline is 4. The description adds value by enumerating the returned fields (status, target quota, completes, CPI, total, country), which helps an agent understand what the listing provides.
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 it lists surveys in the active workspace, with a specific verb and resource. It also provides scoping (active workspace) and details about the returned fields. It does not explicitly differentiate from sibling list_* tools, but the resource (surveys) is distinct and the context makes it obvious.
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 it (to get surveys in the active workspace) but does not explicitly state when not to use it or mention alternatives. It provides no exclusions, but the context of sibling tools (e.g., list_questions, list_completes) makes the intended usage clear. Lacks explicit guidance but is not misleading.
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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