List all teams in your organization. Shows team name, member count, project count, and description.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "list_teams"
}
}| 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?
With no annotations provided, the description carries the burden of behavioral disclosure. It does state the output fields (team name, member count, project count, description), which is useful. However, it does not mention any limitations such as pagination, ordering, or whether archived teams are included. It also does not explicitly confirm that this is a read-only operation, though 'List' implies it.
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 opens with the verb 'List' and immediately defines the resource and scope. It includes the key output fields without any extraneous words. Every word contributes useful information, making it highly efficient.
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 simplicity (no parameters, no output schema), the description is quite complete. It explains what the tool does and what data is returned. However, it omits any caveats (e.g., whether all teams are returned at once, or whether special permissions are required) that could be relevant for an agent. Overall, it's adequate for the tool's low complexity.
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 tool has 0 parameters, so there is no parameter semantics to explain. Per the rubric, a baseline of 4 applies when no parameters are present. The schema is empty, and the description correctly omits parameter details since none exist.
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 the tool's function: 'List all teams in your organization.' It specifies the resource (teams), the scope (all teams in org), and the returned fields (team name, member count, project count, description). This distinguishes it from sibling tools like list_project_teams, which focus on teams within a specific project.
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 phrase 'all teams in your organization' implies when to use this tool (for a broad org-wide listing) and indirectly suggests that for a single team, get_team_details might be more appropriate. However, no explicit alternatives or exclusions are mentioned, leaving some ambiguity for agents comparing sibling tools.
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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