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Update Entity

update_entity

Update an entity's name, description, external_entity_id, and/or attributes.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "entity_id": "<entity_id>"
    },
    "name": "update_entity"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameNoOptional new entity name.
api_keyNoCatchAll API key. Optional if provided via x-api-key header or CATCHALL_API_KEY env var.
entity_idYesThe entity ID to update.
descriptionNoOptional new description.
external_entity_idNoOptional customer-supplied identifier linking this entity to an external system's record (new in 1.6.3).
additional_attributesNoOptional updated structured attributes (see `create_entity` for the company_attributes shape).

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
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 of behavioral disclosure. It only says 'update' which implies mutation, but fails to disclose whether the operation is idempotent, what happens if the entity doesn't exist, permission requirements, or error handling. This is a significant gap for a mutation tool.

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, concise sentence that front-loads the action and key fields. It is efficient with no wasted words, though it could have been slightly more informative without losing conciseness.

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?

For a mutation tool with no annotations and an output schema present, the description is too sparse. It doesn't explain return values, error conditions, idempotency, or any behavioral nuances. An agent calling this tool would have no idea what to expect beyond the basic update action.

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 each parameter is already documented in the schema. The description adds minimal value beyond listing the fields, which the schema already covers. It does not add any extra semantic meaning or clarify parameter relationships.

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 clearly states the action (update) and resource (entity) and explicitly lists the fields that can be modified (name, description, external_entity_id, attributes). It is specific and distinguishes itself from other update_* siblings by targeting entities, even though it doesn't explicitly contrast with them.

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 create_entity or other update tools. It doesn't mention prerequisites like entity existence, nor does it specify conditions for using this over alternatives. Usage context is entirely implicit.

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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