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coval-ai

Coval MCP Server

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by coval-ai

get_agent

Retrieve configuration details for a specific agent, including model type, phone number, endpoint, and display name.

Instructions

Get agent config: model_type, phone_number (voice), endpoint (websocket/chat), and display_name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesThe unique ID of the agent to retrieve. Get this from list_agents.
Behavior2/5

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

With no annotations, the description carries full burden for behavioral disclosure. It only lists returned fields, omitting traits like idempotency, error handling, authorization needs, or whether this triggers side effects. For a read tool, this is minimal but still insufficient.

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 under 20 words that front-loads the purpose. It earns its place with specific return fields. Slightly under 5 because it could be even more concise, but overall excellent.

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

Completeness4/5

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

For a simple getter with one parameter, no output schema, and a list of siblings, the description is nearly complete. It lists important return fields, helping the agent understand output shape. Could be improved by mentioning null handling or error cases, but sufficient.

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 coverage is 100% and the parameter description already explains 'agent_id' (unique ID from list_agents). The tool description adds no extra meaning beyond what the schema provides, so baseline of 3 is appropriate.

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

Purpose5/5

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

The description uses a specific verb ('Get') and resource ('agent config'), and lists exact return fields (model_type, phone_number, endpoint, display_name). This clearly differentiates it from sibling tools like list_agents (list all) and create_agent (create new).

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

Usage Guidelines3/5

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

The description implies use when needing a specific agent's configuration, but lacks explicit guidance on when to use this versus alternative tools like list_agents or other getters (get_persona, get_metric). No exclusions or when-not-to-use are provided.

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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