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trigger_transformation

Start a dbt transformation run by ID and optionally wait for completion. Returns the run status, including failure details or timeout, so you can monitor and verify pipeline execution.

Instructions

Trigger a transformation run.

Write tool: available only when this session was granted write access — the local server's --allow-write flag, or an OAuth consent in which the user approved write. Read-only sessions refuse it.

Args: transformation_id: The transformation to run. wait: If true, block until the run completes (up to 120s). The result is returned either way -- a run that FAILED comes back as {"status": "failed", "error_message": ...}, not as an error. Check status; do not assume a returned result means success. A wait that times out returns {"timed_out": true} with the run still going.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNo
transformation_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses write authorization requirements, refusal in read-only sessions, blocking up to 120s, failure results returned as status fields rather than errors, and timeout behavior with the run continuing. This goes far beyond the schema.

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?

The purpose is front-loaded, the write-access caveat is placed early, and the Args section is tightly scoped. Every sentence adds information; no filler.

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?

Given there are no annotations and no schema-level descriptions, the text covers the essential operational context: authorization, side effect, parameter behavior, and the non-exception failure modes. The output schema exists, so return-value details need not be restated.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It explains transformation_id as the transformation to run and gives rich semantics for wait: blocking up to 120s, failure/timeout result shapes, and instruction to check status rather than assume success. This is exactly the missing meaning.

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 opens with 'Trigger a transformation run,' a specific verb and resource, and the args clarify it acts on a transformation_id. It doesn't explicitly contrast with sibling trigger tools like trigger_pipeline, but the resource is unambiguous.

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?

It states a clear precondition: it is a write tool available only with write access, and read-only sessions refuse it. It doesn't name alternatives or say when to prefer this over trigger_pipeline/compile_transformation, but the context is explicit enough.

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