get_agent_detailFull detail on one expert agent by slug (from list_agents): role, description, default model, domain, tags, and tools.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The agent slug, e.g. 'safety_officer'. |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -{
- "additionalProperties": false,
- "properties": {
- "text": {
- "type": "string"
- }
- },
- "required": [
- "text"
- ],
- "type": "object"
-}New value: +nullDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description does not need to restate safety. The description adds value by specifying what data is returned, but it does not disclose behavior for invalid or missing slugs, or any limits on the 'full detail' claim. With annotations covering the safety profile, this is adequate but not exceptional.
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, front-loaded sentence that conveys the tool's purpose, input source, and returned content. There is no filler or redundant restatement of the tool name.
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 read-only lookup with one required parameter, strong annotations, and no output schema, the description is complete. It names the input source, the fields returned, and the scope ('one expert agent'). Nothing critical is missing for an agent to invoke it 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?
Schema coverage is 100% and the schema describes the slug parameter with an example. The description adds meaningful context by explaining that the slug comes from list_agents, which helps the agent know how to source a valid value. This goes slightly beyond the schema baseline.
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 names a specific verb and resource ('Full detail on one expert agent by slug') and lists the returned fields (role, description, default model, domain, tags, tools). It distinguishes itself from list_agents by making clear this is the per-item detail lookup rather than a list.
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 'by slug (from list_agents)' clearly implies the intended usage: first call list_agents to obtain a valid slug, then call this tool for detailed information on that single agent. It does not explicitly state exclusions or alternatives, but the context is sufficient for correct selection.
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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