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Runn: create workstream

runn_create_workstream

Create an account-level workstream to organize bands of work, then attach it to projects and allocate assignments by workstream ID.

Instructions

Create a workstream (POST /workstreams). Workstreams are account-level bands of work; create one, then attach it to a project with runn_add_project_workstream. To allocate work to it, pass its id as workstreamId on runn_create_assignment / runn_bulk_actuals. Assignments on the SAME person/role but DIFFERENT workstreams may overlap (Runn sums the load).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesWorkstream name (e.g. a course or stream of work).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.2.1

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well by disclosing that workstreams are account-level, that assignments on the same person/role but different workstreams may overlap (Runn sums the load), and that the created id is used for later allocation. This is meaningful behavioral context beyond a simple 'create' statement, though it doesn't detail return formatting or error conditions.

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 sentences, front-loaded with the action. Each sentence provides distinct value: the HTTP endpoint, the definition and next step, the allocation path, and a caveat about overlap. No fluff or repetition.

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?

For a simple one-parameter create tool with no output schema, the description covers purpose, workflow, and a key behavioral nuance. It doesn't state what the response includes, but for a create the returned object with id is implied, and the complexity is low. The description is nearly complete for an agent to invoke and use the result.

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% (the single 'name' parameter has a description). The tool description adds context about what a workstream is and how the id is used, but it does not elaborate further on the 'name' parameter itself. Baseline 3 is appropriate because the schema already documents the parameter.

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 opens with 'Create a workstream (POST /workstreams)' — a specific verb and resource. It also defines a workstream as 'account-level bands of work' and distinguishes it from related create tools (project, phase, milestone) by clarifying that a workstream is attached to a project later via runn_add_project_workstream.

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

Usage Guidelines4/5

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

The description gives clear sequential context: 'create one, then attach it to a project' and 'To allocate work to it, pass its id as workstreamId on runn_create_assignment / runn_bulk_actuals.' It does not explicitly state 'use this instead of X' or mention exclusions, but the workflow context is strong enough to guide correct usage.

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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