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RunWhen Platform MCP

Get Assistant

get_assistant

Fetch a single AI assistant persona by short name and workspace, returning its full configuration for RunWhen Platform coding-agent tasks.

Instructions

Get a single AI assistant (persona) by its short name (full config).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assistant_nameYesAssistant short name (e.g. 'azure-devops'). Workspace prefix optional.
workspace_nameYesThe workspace to query (e.g. 't-oncall').

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. 'Get' implies a read, and 'full config' hints that the complete configuration is returned, but it says nothing about required permissions, error behavior for unknown assistants, or rate limits. This is thin for an un-annotated tool.

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

Conciseness5/5

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

A single tightly constructed sentence with the action, resource, lookup key, and return depth front-loaded. There is no filler, and every clause earns its place.

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?

An output schema exists, so return values need not be described, and the schema fully documents both parameters. The description is adequate for a simple two-parameter read tool but omits any usage routing or behavioral context that an agent would need when weighing this against its many siblings.

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%, with both assistant_name and workspace_name documented, so the baseline is 3. The description's 'short name' wording mirrors the schema's documented example format and adds no new syntax or format detail beyond it.

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?

States a specific verb (Get) and resource (a single AI assistant/persona) and clarifies the lookup key (short name) plus the depth of the return (full config). It implicitly distinguishes itself from list_assistants by specifying 'a single', but never names a sibling explicitly.

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 when-to-use guidance, no mention of prerequisites, and no named alternative. The 'by its short name' phrasing weakly implies a lookup-when-you-know-the-name pattern, but nothing tells the agent when to choose this over list_assistants or get_workspace_context.

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