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comfy_inspect_workflow

Read-onlyIdempotent

Scans a ComfyUI workflow JSON to identify custom node classes, separating stock from custom types, and reports a trust level to warn users before executing untrusted workflows.

Instructions

Enumerate custom (non-stock) node class types in a workflow.

Workflow JSON is arbitrary code - custom nodes run Python on the ComfyUI server. This tool surfaces which class_types are NOT in the set of ComfyUI core / first-party node patterns, so an agent can warn the user (or refuse to auto-queue) before submitting a workflow from an untrusted source.

Returns a JSON report with trust_level (stock | mixed | fully_custom), the stock + custom class lists, and per-warning strings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workflowYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare read-only and idempotent behavior. The description adds meaningful context beyond that: workflow JSON can run arbitrary Python, and the tool surfaces non-stock class_types for security triage. It also explains the trust_level output semantics without contradicting the annotations.

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?

Three tightly scoped paragraphs: a purpose sentence, a concise security rationale, and a summary of the return report. Every sentence earns its place with no repetition of annotation fields.

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?

The description covers the tool's purpose, when to use it, security motivation, and output report shape. An output schema exists for structural details. It could explicitly exclude sibling alternatives, but for a moderately simple analysis tool, it is sufficiently complete.

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?

The input schema has one opaque 'workflow' object with no property descriptions and 0% schema coverage. The description identifies it as workflow JSON and mentions class_types, but does not explain the expected node/class_type structure, so the description only partially compensates for the schema's silence.

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 first sentence uses a specific verb 'Enumerate' and a precise resource: 'custom (non-stock) node class types in a workflow.' This clearly distinguishes it from sibling tools like comfy_validate_workflow or comfy_list_node_types.

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?

The description gives clear context: use this tool before submitting workflows from untrusted sources, to warn the user or refuse to auto-queue. It does not explicitly name alternatives or list when-not-to-use scenarios, so it stops short of a perfect 5.

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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