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validate_workflow

Read-only

Validate a workflow WITHOUT running it (no side effects). Per node: config vs Pydantic model + JSX/placeholder lint, missing required fields, reference validity, and whether a required credential is attached. Runs the SAME checks update_workflow surfaces inline per touched node — use the inline verdict while building, and validate_workflow as the final gate before run_workflow. Returns: {nodes: [{node_id, type, operation, config_valid, validation_error?, missing_required?, reference_warnings?, credentials_missing?, credentials_disconnected?}]}. credentials_disconnected means an ATTACHED credential's provider session is dead (e.g. WhatsApp phone unlinked) — the fix is reconnecting that credential, never creating a duplicate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
node_idsNo
workflow_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

The description explicitly notes no side effects, aligns with the readOnlyHint annotation, and explains the meaning of credentials_disconnected and the proper fix, making behavior transparent.

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?

The description is dense but well-structured, covering purpose, return shape, and an important edge case, though it is slightly longer than strictly necessary.

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

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description gives good operational context and return-shape details, but the missing parameter explanations leave the overall context incomplete for fully correct invocation.

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

Parameters2/5

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

The schema provides no descriptions for workflow_id or node_ids, and the description does not explicitly explain how node_ids affects validation or what workflow_id refers to, leaving parameter semantics under-specified.

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 clearly states the tool validates a workflow without running it, provides a specific verb and resource, and distinguishes it from run_workflow and update_workflow.

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?

It explicitly says to use the inline verdict while building and validate_workflow as the final gate before run_workflow, and contrasts with update_workflow, giving clear when-to-use guidance.

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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