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comfyui_set_input

Set a literal node input value - such as prompt text, seed, dimensions, or model name - in a ComfyUI workflow.

Instructions

Set a literal node input such as prompt text, seed, dimensions, or model name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYes
node_idYes
input_nameYes
workflow_nameYes
expected_revisionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description must carry the full burden of behavioral disclosure, but it only states the basic action. It does not mention that the tool modifies a workflow, how expected_revision affects concurrency, whether validation occurs, or any side effects. This is a significant gap for a mutation tool.

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 a single, well-structured sentence that is front-loaded with the action and resource, followed by concrete examples. Every part adds value, with no wasted words.

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

Completeness2/5

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

The tool has 5 parameters, an output schema, and is a mutation tool with no annotations, but the description gives no contextual details about modifying workflows, optimistic locking via expected_revision, or relationships to other editing tools. The output schema reduces the need to describe return values, but the missing behavioral and usage context makes the description incomplete.

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 schema has 0% description coverage, so the description must compensate. It adds useful context for the 'value' parameter by listing example literal inputs, but it does not explain workflow_name, node_id, input_name, or especially expected_revision. The parameter names are self-explanatory, but the description only partially compensates for the missing schema descriptions.

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 uses a specific verb ('Set') and resource ('literal node input') with clear examples (prompt text, seed, dimensions, model name), and distinguishes itself from sibling tools like comfyui_connect_nodes by emphasizing 'literal'. It clearly states what the tool does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'literal node input' implies the tool is for setting direct parameter values rather than connections, and the examples suggest common use cases. However, there is no explicit when-to-use guidance or mention of alternatives like comfyui_connect_nodes, so the guidance remains implied rather than explicit.

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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