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Coalesce-Software-Inc

coalesce-transform-mcp

Official

COA Dry Run Run (DML preview)

coa_dry_run_run
Read-onlyIdempotent

Preview the DML that coa run would execute without hitting the warehouse. Run offline against local project files to validate SQL templates before deployment.

Instructions

Preview the DML that coa run would execute, without hitting the warehouse. Forces --dry-run --verbose.

Runs entirely offline against local project files — no Coalesce cloud authentication or API calls. coa run (and coa create) are the offline local-dev commands; do not confuse with the scheduler-aware coa deploy / coa plan / coa refresh which target cloud environments.

OUTPUT SHAPE (CD-16959+): dry-run reports pass/fail for every selected node rather than stopping at the first template error. Scan the full stdout — a non-zero exit code means one or more nodes failed, but successful nodes still render their generated SQL above/below the failures.

LIMITATION: dry-run only exercises the SQL generator. It does NOT validate that referenced columns or types exist in the actual warehouse — a dry-run can succeed with column references that will fail at run-time with 'invalid identifier'. Use cortex or another Snowflake-capable MCP to confirm the schema when that matters.

Args:

  • projectPath (string, required)

  • workspace (string, optional)

  • include / exclude (string, optional): Node selector

Returns: { command, exitCode, stdout, stderr, coaVersion }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
excludeNoCOA node selector to exclude.
includeNoCOA node selector, e.g., '{ STG_ORDERS }' or '{ location: "SRC" }'. See `coa describe selectors`.
workspaceNoCOA workspace name from workspaces.yml. Defaults to 'dev'.
projectPathYesAbsolute or relative path to the COA project root (the directory containing data.yml).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
jsonNo
stderrYes
stdoutYes
commandYes
exitCodeYes
timedOutYes
coaVersionYes
jsonParseErrorNo
preflightWarningsNo
Behavior5/5

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

Description adds significant value beyond annotations: it reveals offline nature, no authentication needed, output shape (pass/fail per node), non-zero exit code meaning, and limitation that dry-run doesn't validate column/type existence. Annotations already indicate read-only and idempotent, but description enriches with operational details.

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?

Description is well-organized with sections (OUTPUT SHAPE, LIMITATION) and concise bullet points. Every sentence adds value, no redundancy.

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?

Despite formal output schema not fully detailed, description explains output shape, exit code interpretation, and limitations. Covers key aspects needed for correct use: offline, no auth, column validation caveat. Comprehensive for a dry-run 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?

Input schema has 100% description coverage, so description adds minimal new meaning. It gives examples for include/exclude but mostly restates schema. Baseline 3 is appropriate.

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?

Description clearly states it previews DML from `coa run` without hitting warehouse, forcing --dry-run --verbose. It distinguishes from sibling tools like coa_dry_run_create and coa_run, and clarifies it's offline vs cloud commands.

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?

Explicitly warns not to confuse with coa deploy/plan/refresh, tells when to use cortex for schema validation, and advises to scan full stdout for exit codes. Provides clear context for when to use this tool vs alternatives.

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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