RunWhen Platform MCP

Search Workspace

search_workspace

Finds tasks, resources, and configuration in a workspace via lightweight autocomplete, useful as a fallback when full semantic search is not needed.

Instructions

Search for tasks, resources, and configuration in a workspace.

Uses the workspace's task search / autocomplete to find matching items.

NOTE: Prefer workspace_chat for most search queries — it uses semantic search and keyword grep across issues, resources, SLXs, and run sessions with much richer results. Use this tool only as a lightweight autocomplete fallback.

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": {
      "query": "<query>",
      "workspace_name": "<workspace_name>"
    },
    "name": "search_workspace"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes	Search query string.
`workspace_name`	Yes	The workspace to search (e.g. 't-oncall').

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 7, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description must carry the behavioral burden; it discloses the mechanism (task search/autocomplete) and positions itself as a lightweight fallback versus the richer semantic search of workspace_chat. It does not mention auth, rate limits, or result scope beyond the autocomplete framing, so it is strong but not exhaustive.

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?

Front-loads the core purpose, then the mechanism, then a clearly delimited NOTE carrying the routing advice. Every sentence earns its place with no filler.

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

Completeness4/5

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 no explanation, and the two params are fully covered by the schema. The description supplies purpose, mechanism, and sibling routing, leaving only minor unstated details (e.g. result limits) for a low-complexity search tool.

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 coverage is 100%, so both query and workspace_name are already documented in the schema, making 3 the baseline. The description adds no syntax, format, or matching-behavior detail for the parameters beyond what the schema provides.

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?

States a specific verb (Search) and resource (tasks, resources, and configuration in a workspace), then clarifies the underlying mechanism as task search/autocomplete. It explicitly names and differentiates itself from the sibling workspace_chat, so an agent can disambiguate without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit alternative ('Prefer workspace_chat for most search queries'), the reason for that preference (semantic search + keyword grep with richer results), and the specific condition for using this tool ('only as a lightweight autocomplete fallback'). When-to-use, when-not, and the alternative are all present.

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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