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enable_assistant

Activate an AI assistant by ID so it can receive delegated tasks. Use this to prepare assistants for asynchronous task handoff and management.

Instructions

Enable an assistant so it can receive delegated tasks.

Args: assistant_id: Assistant id.

Returns: JSON result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assistant_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral burden. It does disclose the state change's effect (assistant becomes able to receive delegated tasks), which is useful, but it says nothing about idempotency, permissions, reversibility, or side effects on existing tasks.

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 first sentence is short and front-loaded, but the boilerplate 'Args:' / 'Returns: JSON result.' block is pure noise — the arg doc is tautological and the return note is redundant given an output schema exists.

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?

For a simple one-parameter mutation with an output schema, the description is minimally adequate: the effect is stated and the return format need not be explained. However, with zero annotation coverage it leaves permission, idempotency, and failure behavior unaddressed.

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

Parameters2/5

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

Schema coverage is 0% and the description's only parameter note is 'assistant_id: Assistant id.' — a tautological restatement of the property name that adds no meaning (format, where to obtain the id, or optionality). It does not compensate for the coverage gap.

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 opening sentence gives a specific verb (Enable) and resource (assistant) plus the functional consequence ('so it can receive delegated tasks'), which cleanly distinguishes it from disable_assistant. It stops short of naming siblings explicitly, but the action is unambiguous.

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?

Usage is only implied via the consequence clause — the agent can infer this is the counterpart to disable_assistant. There is no explicit when-to-use, no precondition (assistant must already exist/be disabled), and no stated alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.