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Particle-Academy

fancy-flow-mcp-js

Get Workflow

get_workflow

Retrieve a workflow's complete node-and-edge graph for authoring: each node includes kind, config, and parentId, and all edges are listed. Use this to inspect or modify a workflow's structure.

Instructions

Return one workflow's full graph — every node with its kind, config and parentId, and every edge. This is the authoring view; use export_workflow for the portable WorkflowSchema document.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workflow_idYesThe workflow id from create_workflow.

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of disclosing behavior. It clearly states the tool returns the entire graph, listing every node's fields and every edge, which makes the read-only nature of the operation implicit. It does not explicitly say 'no side effects' or address error cases (e.g., nonexistent workflow_id), but its email definition is largely transparent and adequate for the task.

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 description is compact and front-loaded: it states the core action and resource in the first sentence, then offers a useful contrast with export_workflow in the second. There is no filler, and each clause contributes a distinct fact.

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?

For a one-parameter retrieval tool with no annotations and no output schema, the description fully covers what an agent needs: the exact return contents (nodes with all specified fields and edges) and a clear conceptual category (authoring view). Nothing essential is missing for safe and correct invocation.

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 description coverage is 100%, with workflow_id documented as 'The workflow id from create_workflow.' The description itself adds no new parameter-specific information, meaning it does not compensate beyond the schema. Since the schema already covers the single parameter, the 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?

The description opens with the specific verb 'Return' and a precise resource ('one workflow's full graph'), then adds concrete detail ('every node with its kind, config and parentId, and every edge'). It goes further by naming the sibling tool it is not ('use export_workflow for the portable WorkflowSchema document'), making it instantly distinguishable from other workflow tools without needing to inspect their schemas.

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?

The description provides an explicit alternative: 'This is the authoring view; use export_workflow for the portable WorkflowSchema document.' This tells an agent exactly when to call get_workflow (need the editable graph representation) versus when to use a sibling, leaving no ambiguity about the decision boundary.

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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