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photo_upscaler

Image Upscaler — Enlarge an existing image 2x or 4x with super-resolution detail recovery, with an optional face-enhancement pass. Sharpens and upsizes a user-supplied photo; does not generate new imagery. [category: photo]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileYesHard 10 MB cap (400 above it). JPG/PNG/WebP/BMP only — no GIF/HEIC. Big images risk the 120s upscale timeout.
modelNofast (default) — ~16s at any scale, softer on very fine texture. quality — best fine detail but 50s at 2x and 245s at 4x on CPU; expect a wait.fast
scaleNoUpscale factor; invalid values silently fall back to 2. With the default fast model 4x costs the same as 2x.
face_enhanceNoRun the additional face-enhancement pass.
output_formatNoOptional output format; defaults to the input format.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / model / x-ui
      Added value: +{
+  "labels": {
+    "fast": "Fast — about 15 seconds",
+    "quality": "Best detail — up to 4 minutes"
+  }
+}
    • changedInput schema / properties / output_format / enum
      Previous value: -[
-  "jpg",
-  "jpeg",
-  "png",
-  "webp"
-]New value: +[
+  "jpg",
+  "png",
+  "webp"
+]
  2. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=false), and the schema carries the real behavioral detail (timeouts, model speeds, invalid-value fallback). The description's only extra behavioral signal is 'does not generate new imagery', so it adds modest value on top of structured fields.

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?

Three tight sentences with zero filler, front-loading the core action and immediately following with the key scope exclusion. The category tag is compact and placed last.

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?

With no output schema, the description could state what it returns (an upscaled image file, and in which format), which would matter for downstream chaining. Otherwise the purpose, scope, and behavior are adequately covered given the rich input schema and annotations.

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?

Schema description coverage is 100%, so every parameter (file, model, scale, face_enhance, output_format) is already documented in the schema with enum labels and defaults. The description repeats the 2x/4x scale and optional face-enhancement pass but adds no syntax or constraint beyond the schema, so the baseline 3 applies.

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 pairs a specific verb and resource ('Enlarge an existing image 2x or 4x with super-resolution detail recovery') and explicitly carves out scope with 'does not generate new imagery', which separates it from generate_* tools. An agent can distinguish it from plain photo_resize via the stated super-resolution/detail-recovery behavior.

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?

It gives one implicit when-not ('does not generate new imagery'), useful for avoiding generation tools, but offers no explicit guidance on when to choose this over the closest sibling photo_resize, nor any prerequisites. Usage is only implied.

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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