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Hermoso

Hermoso

Official
by hermoso-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

Edit an image

edit_image

Modify an existing image in place with plain-language instructions while preserving composition, aspect ratio, people, and untouched text.

Instructions

EDIT an existing image in place with a plain-language instruction and keep everything else: 'make the headline bigger', 'add our logo bottom right', 'swap the background for a kitchen', 'remove the person on the left', 'erase all the text'. Pass image (URL, Library item, upload_file URL or local path) and instruction. The same edit the web Studio's Edit runs: composition, aspect ratio, people and every untouched line of text stay as they are; the saved brand's real name and website are pinned so an added line never invents one, and the brand's real logo is attached when the instruction asks for the logo. Set removal:true when the edit STRIPS text, branding or an object, so nothing branded is put back. When the saved brand has a product photo and the ad shows that product, the photo rides with the edit and the product's label is read and checked against it: re-printed from the photo only when it came out wrong (the check alone is charged when it is right; one small extra charge finds the product first). fixLabel:false turns that off. For a precise region, pass mask (see generate_image). One image edit's credits; returns the new image URL. For a new image from a prompt use generate_image; to rebuild a competitor's ad for your brand use clone_static.

Input Schema

NameRequiredDescriptionDefault
maskNooptional mask image (URL or local path) marking the region to change: transparent = change, or white = change on an opaque mask
imageYesthe image to edit: URL, Library item URL, upload_file URL or local path
dryRunNotrue = return what this edit usually costs in credits and render nothing
removalNotrue when the edit REMOVES text, branding, a logo, a watermark, a person or an object, so the brand name and logo are not re-added
fixLabelNofalse = leave the product label exactly as rendered: no product lookup, no label check, no re-print (default on when the ad shows the brand’s saved product)
instructionYesthe change to make, in plain words (pass the user’s own words for a removal or plain photo edit)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.484
    • changedInput schema / properties / dryRun / description
      Previous value: -"true = return the estimated credits this edit reserves and render nothing"New value: +"true = return what this edit usually costs in credits and render nothing"
  2. Changed1 schema field changedv0.1.435
    • changedInput schema / properties / dryRun / description
      Previous value: -"true = return the exact credits this edit reserves and render nothing"New value: +"true = return the estimated credits this edit reserves and render nothing"
  3. Changed1 schema field changedv0.1.366
    • addedInput schema / properties / fixLabel
      Added value: +{
+  "description": "false = leave the product label exactly as rendered: no product lookup, no label check, no re-print (default on when the ad shows the brand’s saved product)",
+  "type": "boolean"
+}
  4. Changed1 schema field changedv0.1.320
    • addedInput schema / properties / dryRun
      Added value: +{
+  "description": "true = return the exact credits this edit reserves and render nothing",
+  "type": "boolean"
+}
  5. Addedv0.1.272

TDQS

A4.6/5.0
Behavior4/5

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

Goes well beyond the annotations: it discloses credit cost, that brand name/website are pinned, that a saved product photo rides along and the label is read and re-printed only when wrong, plus the extra charge for product lookup, and that it returns the new image URL. The only gap is that the dryRun behavior is left to the schema rather than restated in the description.

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?

Front-loaded with the core action and examples, then ordered into conditions (removal, product label, mask, alternatives). It is long and the product-label sentence is dense with nested clauses ('the check alone is charged when it is right; one small extra charge finds the product first'), costing some readability.

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 six-parameter, open-world mutation tool with no output schema, it covers what the agent needs: cost model, return value ('returns the new image URL'), brand-safety behavior, and sibling alternatives. Nothing required to call it correctly is missing.

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

Parameters4/5

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

Schema coverage is 100%, so a 3 is the floor; the description earns above that by explaining the intent behind parameters — what removal:true prevents ('so nothing branded is put back'), what fixLabel:false disables, and that mask should be consulted via generate_image. It adds meaning rather than restating field types.

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?

Opens with a specific verb+resource ('EDIT an existing image in place') and immediately grounds it in concrete example instructions. It also names the two sibling tools it is not (generate_image, clone_static), so the agent can discriminate without opening any schema.

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?

Explicit routing is given: 'For a new image from a prompt use generate_image; to rebuild a competitor's ad for your brand use clone_static.' It further states conditional usage for removal:true, fixLabel:false, mask, and dryRun, so the agent knows when each mode applies.

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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