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Glama

Upscale an image

carpe_image_upscale

Increase an image's resolution by 1–4× from a URL, data URI, or local path to prepare source images (256×256 or larger) for higher-detail use.

Instructions

Increase image resolution 1–4× (source ≥ 256×256). Always on /v1. image: https URL, data: URI or local path (stdio).

Input Schema

NameRequiredDescriptionDefault
extraNoAdditional model parameters passed through verbatim (steps, cfg_scale, style_preset, hide_watermark…).
imageYes
modelNoDefault "upscaler".
scaleNoDefault 2.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false and openWorldHint=true. The description adds genuine context beyond them: the fixed /v1 endpoint, the minimum source size, and the accepted input transports including stdio local paths. It does not say whether the job is synchronous or requires polling carpe_image_status, nor what the output looks like, which is a meaningful gap given no output schema.

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?

Three terse fragments, front-loaded with the operation and scale range, with zero filler. The telegraphic style ("/v1.", "(stdio)") is efficient but slightly cryptic for a first-time reader.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-parameter, open-world mutating tool with no output schema, the description covers input adequacy well but leaves the response unexplained (upscaled image URL vs. base64 vs. job ID) and never mentions async/status polling despite carpe_image_status being a sibling. An agent could invoke it correctly but may not know how to retrieve or interpret the result.

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 75% and the undescribed parameter is exactly `image`, which the description clarifies (https URL, data: URI, or local path over stdio). It also restates the 1–4 scale bound with the source-size floor, adding a real constraint. This is meaningfully above the schema-only baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Increase image resolution 1–4×" names a specific verb (increase resolution) and resource (image) with a quantified output range, which is clearly distinct from sibling generators like carpe_image_generate or carpe_image_edit. It does not explicitly name those siblings or state the boundary, so it stops short of a 5.

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?

The source constraint ">= 256×256" implies when the tool is applicable and implies the input must already be an existing image (vs. generation). However, there is no explicit statement of when to use this versus carpe_image_edit / carpe_image_multi_edit, and no mention of alternatives for sources below the size floor.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.