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AetherWave-Studio

Aetherwave Studio

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by AetherWave-Studio
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JavaScript
Remote

Edit image with AI (I2I)

aetherwave_edit_image

Edit an existing image using a text prompt. Submit a public image URL and describe the change to receive edited versions.

Instructions

Edits an existing image guided by a text prompt. Pass a public imageUrl plus a prompt describing the change ("add a moon to the sky", "swap the background for a neon city", "make it look like a comic panel"). Submits, polls, and returns the edited image URL(s). Default model is 'grok-imagine-i2i' (6 cr per call, returns 2 variations, ~30s, best cost-to-quality on standard edits). Other I2I-capable models: 'seedream-v4-edit', 'wan-2.5-spicy-i2i', 'flux-kontext-pro', 'qwen-image-edit', 'gpt-image-1.5-i2i' (slow, ~5min). Use list_image_models for full lineup. Note: source URLs with spaces or parentheses may fail upstream; prefer clean URLs.

Model selection guide for edits

Default: grok-imagine-i2i (6 cr per call, returns 2 variations = 3 cr/image effective, fast ~30s, strong general-purpose edit quality).

Pick a different model when:

  • Need a single deterministic output, or 4K resolution -> seedream-v4-edit (7 cr per image, supports 1K/2K/4K, multi-image up to 6)

  • Subtle edits / preserve composition / character consistency -> flux-kontext-pro or flux-kontext-max

  • NSFW edits -> wan-2.5-spicy-i2i

  • Highest quality, time is not a concern (~5 min OK) -> gpt-image-1.5-i2i or grok-imagine-quality-i2i (16 cr @ 1K, 22 cr @ 2K)

  • Stylized / artistic transformation -> midjourney-i2i

If the user simply says "edit this image" with no other signal, default to grok-imagine-i2i.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesText description of the edit (e.g. 'replace the sky with sunset clouds').
imageUrlYesPublic URL of the source image to edit. Must be a real, fetchable URL.
modelNoModel ID. Defaults to 'grok-imagine-i2i' (3 cr/image effective, 2 outputs). Other options: 'seedream-v4-edit', 'wan-2.5-spicy-i2i', 'flux-kontext-pro', 'qwen-image-edit', 'gpt-image-1.5-i2i', 'grok-imagine-quality-i2i'. Use list_image_models for the full list.
aspectRatioNoOutput aspect ratio (e.g. '1:1', '16:9'). Defaults to the source ratio for most models.
resolutionNoOutput resolution. Tiered-pricing models accept '1K' / '2K'.
qualityNoQuality preset for models that support it (e.g. GPT Image 2).
maxImagesNoNumber of variations to return for multi-output models.
renderingSpeedNoRendering speed preset for models that support it.
negative_promptNoWhat to avoid in the output (supported by some models).

Tool Definition Quality

A4.9/5.0
Behavior5/5

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

Discloses submission, polling, and return of edited image URLs. Includes cost (6 cr per call), time (~30s), and failure modes (URLs with spaces/parentheses). No contradiction with annotations (readOnlyHint=false, openWorldHint=true).

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?

Well-structured with headings and bullet points. Every sentence adds value. Slightly long but justified by complexity. Front-loaded with core action, then detailed model guide.

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 9 parameters, openWorldHint=true, and no output schema, the description is thorough. Explains return behavior, default model, cost, time, and caveats. Covers all needed context for an agent to use correctly.

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

Parameters5/5

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

Despite 100% schema coverage, description adds significant value: explains default model, cost, output count, speed, and model trade-offs. For imageUrl, warns about clean URLs. For model, provides detailed usage scenarios beyond schema.

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?

Title and description clearly state it edits an existing image using AI with a text prompt. The verb 'edit image' and resource 'public imageUrl plus prompt' are specific. Distinguishes from siblings like generate_image, remove_background, etc.

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?

Provides an explicit model selection guide with when to use each model, default behavior, and fallback. Includes a concrete instruction: 'If the user simply says "edit this image" with no other signal, default to grok-imagine-i2i.'

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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