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Start a Task run

workbench_tasks_start

Kicks off a run of a Task. When the task expects an input document (its trigger has an input), pass the user's material as input — pasted text, extracted attachment text, or JSON. Cite the run id back and tell the user what happens next (the run may immediately be waiting on someone).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputNoTrigger payload — the document text / JSON the task starts from.
taskIdYesTask id (from workbench_tasks_list).
workspaceNoWorkspace slug. Personal tokens with no default workspace MUST pass this; tokens with a default can override per call. Ignored for workspace API keys.
approvalIdNoApproval id from a prior needs_confirmation response. Omit on the first call.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false and openWorldHint=true, so the mutation/side-effect profile is covered. The description adds the useful behavioral note that the run 'may immediately be waiting on someone', but omits the approval/needs_confirmation flow and any auth or rate-limit context.

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

Conciseness4/5

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

Two front-loaded sentences with the purpose first and no filler. The trailing instruction to cite the run id and describe next steps is slightly prescriptive but still earns its place as post-call guidance.

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 mutation tool with no output schema, the description covers the primary input semantics and hints at the async run behavior. The approvalId and workspace parameters are handled by the 100%-covered schema, so nothing critical is missing, though the confirmation flow could be clearer.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3, but the description adds real value on the `input` parameter: it explains WHEN to supply it (task trigger has an input) and what forms it takes (pasted text, extracted attachment text, JSON) beyond the schema's terse 'Trigger payload' text.

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 description names a specific verb ('kicks off a run') and resource ('a Task'), so an agent knows this initiates a run. It does not explicitly distinguish itself from nearby siblings like workbench_tasks_act or workbench_tasks_run_view, so it falls short of a 5.

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?

It gives conditional guidance for the input (pass material when the trigger has an input), which is useful. However, it never states when to use this over alternatives such as workbench_tasks_act or workbench_tasks_run_view, leaving selection to inference.

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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