stream_query_usersList/filter users in the app. e.g. filter {"role":{"$eq":"admin"}} or {"id":{"$in":["u1"]}}. GET /api/v2/users.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Sort spec, e.g. [{"field":"created_at","direction":-1}]. | |
| limit | No | Max users (<=100). Default 100. | |
| filter | No | User filter_conditions, e.g. {"role":{"$eq":"admin"}}. Default {} (all users). | |
| offset | No | Pagination offset. |
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
readOnlyHint=true already tells the agent this is a safe read; the description adds the GET /api/v2/users endpoint, which is mildly useful context. It discloses nothing about result size caps, defaulting, or ordering behavior beyond what the schema already states.
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?
One compact sentence plus an inline example and endpoint, front-loaded with the core action. The trailing 'GET /api/v2/users' is arguably noise for an agent that invokes the tool rather than HTTP, but it costs little.
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?
No output schema exists, so the description would ideally hint at the returned user shape, but it says nothing about the response. With full parameter coverage and a readOnly annotation, the definition is adequate for a simple list tool but not rich.
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%, so filter/sort/limit/offset are already documented with examples. The description restates the filter example and adds an $in-style example, a marginal increment over the schema's $eq example, so the 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?
States a clear verb+resource ('List/filter users in the app') and the backing endpoint, so an agent knows it is a read query over the user collection. It does not distinguish itself from the nearby stream_query_members sibling, whose distinction from 'users' an agent would have to infer.
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?
Usage is implied by 'List/filter users' but there is no explicit when-to-use, when-not, or named alternative (e.g. members vs users, or search tools for text matching). The agent must infer the context.
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.