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generate_with_ip_adapter

Generate images that adopt the style or subject of a reference image while following your text prompt, using IP-Adapter.

Instructions

Generate an image guided by a reference image's style/subject via IP-Adapter, plus a text prompt. Requires the ComfyUI_IPAdapter_plus custom nodes. Upload the reference first with upload_image, then pass its filename as reference_image. Unspecified params fall back to your defaults; checkpoint auto-resolves. Returns prompt_id immediately; asset_id arrives in the completion notification. Requires a running ComfyUI with ComfyUI_IPAdapter_plus and a matching IP-Adapter model installed, or the workflow will fail at execution time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesPositive text prompt
reference_imageYesFilename of the (already-uploaded) reference image in ComfyUI's input dir
weightNoIP-Adapter influence on the output, typically 0.0-1.0 (default 0.8); higher = closer to the reference
presetNoIPAdapterUnifiedLoader preset (default 'PLUS (high strength)')
negative_promptNoNegative prompt (default: empty / from defaults)
widthNoImage width in pixels
heightNoImage height in pixels
stepsNoSampling steps
cfgNoCFG scale
samplerNoSampler name (e.g. euler, dpmpp_2m)
schedulerNoScheduler (e.g. normal, karras)
seedNoSeed (omit to randomize)
checkpointNoCheckpoint filename; auto-selected if omitted
Behavior4/5

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

No annotations are provided, so the description must carry the full burden. It discloses that the tool requires custom nodes (ComfyUI_IPAdapter_plus), that params fall back to defaults, checkpoint auto-resolves, and that it returns prompt_id immediately with asset_id arriving later. It also mentions failure conditions if dependencies are missing. This is transparent for a generation tool with no destructive side effects.

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 five sentences, each adding value: purpose, prerequisites, workflow, behavior, dependencies. It is front-loaded with the main action. While slightly longer than minimal, every sentence earns its place and there is 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?

Given the tool's complexity (13 params, 2 required, no output schema), the description covers purpose, prerequisites, step-by-step workflow, async behavior (prompt_id vs asset_id), default handling, and failure conditions. It provides all necessary context for 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?

All 13 parameters have schema descriptions (100% coverage), so the baseline is 3. The description adds some workflow context (e.g., 'Upload the reference first... pass its filename as reference_image') but does not significantly enhance the semantic meaning of individual parameters beyond what the schema already provides.

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 that the tool generates an image guided by a reference image's style/subject via IP-Adapter, plus a text prompt. It specifies the verb 'generate', the resource 'image', and the method 'IP-Adapter', effectively distinguishing it from siblings like generate_image (no reference) and generate_with_controlnet (different conditioning).

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 provides clear context: it tells when to use this tool (guided by a reference image) and outlines prerequisites (upload reference first, custom nodes, running ComfyUI). It does not explicitly exclude alternatives, but the purpose alone differentiates it among many sibling tools. It also warns about potential failure if dependencies are missing.

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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