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Skysay

Update an AI agent

update_agent
Destructive

Apply the same generic PATCH fields and validation as PATCH /v1/agents/{agent_id}; unknown fields retain REST's no-op compatibility behavior.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo
nameNo
modelNo
toolsNo
voiceNo
statusNo
agent_idYes
languageNo
metadataNo
transcriberNo
translationNo
webhook_urlNo
begin_messageNo
first_messageNo
system_promptNo
audio_stream_urlNo
recording_enabledNo
component_credential_bindingsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.7/5.0
Behavior3/5

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

Annotations already disclose that this is a non-read-only, non-idempotent, destructive operation. The description adds useful behavioral context about PATCH semantics and unknown-field no-op compatibility, but it does not explain destructive effects, permissions, or whether omitted fields are preserved.

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

Conciseness3/5

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

The description is a single efficient sentence with no filler and is front-loaded with the core PATCH behavior. However, its brevity is under-specified for an 18-parameter destructive tool and relies on external REST documentation.

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

Completeness2/5

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

Given 18 parameters, no schema descriptions, no output schema, and a destructive update operation, the description is far too sparse. It adds a useful detail about unknown fields, but it does not provide enough context for an agent to invoke the tool correctly without external API knowledge.

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

Parameters1/5

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

The schema has 18 parameters with 0% description coverage, and the description does not explain any individual parameter. It only refers generically to PATCH fields, leaving the agent unable to infer the meaning and expected values of fields like mode, translator, tools, or metadata.

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 identifies the operation as applying PATCH fields and validation to /v1/agents/{agent_id}, which clearly implies updating an existing AI agent. It distinguishes the operation from creation via PATCH semantics, though it does not explicitly differentiate from all siblings.

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?

There is no explicit guidance on when to use this tool versus alternatives such as create_agent, get_agent, or update_campaign. The PATCH context implies an update use case, but the description provides no when/when-not conditions.

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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