Skip to main content
Glama
runwhen-contrib

RunWhen Platform MCP

Get Workspace Chat Config

get_workspace_chat_config

Fetch the resolved chat rules and commands for a workspace (optionally for a persona) that the workspace chat assistant uses. Returns metadata only.

Instructions

Get resolved chat rules and commands for a workspace.

Returns the list of rules and commands that apply to the workspace (and optional persona). These are the same rules and commands the workspace chat assistant sees. Response includes metadata only (id, name, scope); full rule/command content is not included in this endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
persona_nameNoOptional persona for persona-scoped rules/commands.
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

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose a real limitation: the response includes metadata only (id, name, scope) and not full rule/command content. That is genuinely useful negative information. It stops short of noting auth requirements, scoping behavior, or pagination, but the metadata-only disclosure is a substantive behavioral trait.

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?

Three tight sentences, front-loaded with the core purpose, followed by scope and an important output caveat. No filler and each sentence earns its place.

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

Completeness5/5

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

An output schema exists, so the description need not enumerate return values, and it correctly notes the metadata-only restriction rather than repeating field details. Combined with fully covered parameters, an agent has enough to call this correctly.

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 both workspace_name and persona_name are already documented, including the persona's 'persona-scoped' nature. The description mentions the optional persona but adds no syntax or format detail beyond what the schema provides, so the baseline of 3 applies.

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 (workspace chat config) and clarifies the output is the *resolved* set of rules and commands applying to a workspace/persona. This is a meaningful distinction from siblings like list_chat_rules and list_chat_commands, though it never names those siblings to sharpen the contrast.

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 the use case ('the same rules and commands the workspace chat assistant sees'), which suggests when this aggregated view is preferable to fetching individual rules or commands. However, it never explicitly states when to use this versus list_chat_rules or list_chat_commands, leaving routing to inference.

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