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edit-a-photo

Upload a product photo and make a clean catalog image. Muse Edit preserves the product while changing the background ($0.01/image). Check logos, small details and color against the original before … upload:Product photo -> text:Edit request -> edit:Clean product photo; returns image (muse-image/edit) saved to disk (file path in result). Runs on NanoGPT — $0.18 deposit per call, paid in Nano (XNO) — settles at actual model cost + 20%, change returned; no account needed; last run $0.075, ~80s. Example: Reviewed sample (https://nanoodle.com/examples/gallery/#edit-a-photo). A bottle image edit with its source and instruction documented in the sample. The shape remains recognizable; compare any markings that must survive an edit of your own product.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_payment_idNoPayment id from this tool's previous payment-required response. Phase 3 only: after /x402/watch closes with status paid, call again with the same arguments plus this id to open the RESULTS stream. Do not pass it while payment is still pending — monitor the watch SSE first.
Edit_requestNoText; default: "Prepare this product photo for a catalog. Preserve the exact product shape, color, materials, markings and visible te..."; optional
Product_photoYes* required; image — file path or https URL

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changed
    • addedInput schema / properties / Edit_request
      Added value: +{
+  "description": "Text; default: \"Prepare this product photo for a catalog. Preserve the exact product shape, color, materials, markings and visible te...\"; optional",
+  "type": "string"
+}
    • removedInput schema / properties / Image
      Removed value: -{
-  "description": "* required; image — file path or https URL",
-  "type": "string"
-}
    • addedInput schema / properties / Product_photo
      Added value: +{
+  "description": "* required; image — file path or https URL",
+  "type": "string"
+}
    • removedInput schema / properties / Text
      Removed value: -{
-  "description": "default: \"Rewind this photo into a typhoon night on Taipei's Dihua Street: shuttered Qing-era shophouses, red lanterns thrashin...\"; optional",
-  "type": "string"
-}
    • changedInput schema / required
      Previous value: -[
-  "Image"
-]New value: +[
+  "Product_photo"
+]
  2. Changed1 schema field changed
    • changedInput schema / properties / Text / description
      Previous value: -"default: \"make it night-time, add glowing neon signs and rain reflections\"; optional"New value: +"default: \"Rewind this photo into a typhoon night on Taipei's Dihua Street: shuttered Qing-era shophouses, red lanterns thrashin...\"; optional"
  3. First observed

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the payment flow, the two-phase call pattern (pending vs results), the return of a file path, and the output being saved to disk. It does not mention any destructive side effects, which is reasonable for an image-editing tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is rambling and repetitive, with pricing details, deposit amounts, and the example sentence appearing twice. It mixes core functionality with payment mechanics and example text in a single unstructured block, making it harder to parse quickly. A clearer separation of purpose, pricing, and example would improve readability.

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 essential operational context: what the tool does, what it costs, how payment works (including the two-phase call), what the output is (saved image with file path), and an example. It does not provide an output schema, but the return behavior is described sufficiently for an agent to invoke it correctly.

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?

All three parameters have descriptive comments that go beyond simple naming: Product_photo specifies required file path or URL, Edit_request includes a default instruction, and _payment_id explains the phase-3 behavior and warnings. The schema coverage is 100% and the descriptions add meaningful context.

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 the tool's verb and resource: 'Upload a product photo and make a clean catalog image' with the specific behavior of preserving the product while changing the background. Despite surrounding payment details, the core purpose is unmistakable and distinct from sibling tools.

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?

Some usage context is implied by the catalog-image use case and the advisory to 'check logos, small details and color against the original', but there is no explicit guidance on when to choose this tool over sibling tools or when not to use it. The description focuses more on payment mechanics than on selection criteria.

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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