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get_agent

Retrieve detailed specifications for any AI agent, including input/output schemas, pricing details, and practical usage examples.

Instructions

Get detailed information about a specific AI agent including its input/output schema, pricing, and usage examples.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesThe unique agent ID (e.g. 'gpt-4o-mini')
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It states the tool retrieves information, implying a read-only operation, but doesn't disclose behavioral traits such as authentication needs, rate limits, error handling, or response format. This is a significant gap for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. It could be slightly more structured by separating key details, but it avoids redundancy and wastes no words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It covers what information is retrieved but lacks details on behavioral aspects and usage context. With no output schema, it should ideally hint at return values, but the simplicity keeps it from being severely incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents the single parameter 'agent_id' with its type and description. The description adds no additional meaning beyond what the schema provides, such as examples of valid IDs beyond 'gpt-4o-mini' or constraints. Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('detailed information about a specific AI agent'), including what information is retrieved (input/output schema, pricing, usage examples). It distinguishes from 'list_agents' by focusing on a single agent, though it doesn't explicitly differentiate from 'check_agent_health' or 'invoke_agent'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'list_agents' (for multiple agents) or 'check_agent_health' (for status checks). It implies usage for detailed agent info but lacks explicit when/when-not instructions or prerequisites.

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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