agentsvc-mcp

image_resize

Resize, crop-fit, and convert images (PNG, JPEG, WebP, AVIF, GIF, TIFF, SVG) to WebP, PNG, JPEG, or AVIF. Shrink screenshots for vision models, create thumbnails, or change formats.

Instructions

Image Resize & Convert — Resize, crop-fit and convert images (PNG, JPEG, WebP, AVIF, GIF, TIFF, SVG input) to webp, png, jpeg or avif. Auto-rotates by EXIF. Use to shrink screenshots before sending them to a vision model, create thumbnails, or convert formats. Params: image_base64 or image_url (one required), width, height (max 4096), fit (inside default | cover | contain | fill), format (webp default), quality (1-100, default 80). Cost: $0.0045 USDC per call. Latency p99: 1500ms.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "image_resize"
  }
}

Input Schema

Name	Required	Description	Default
`fit`	No		inside
`width`	No
`format`	No		webp
`height`	No
`quality`	No
`image_url`	No	Public URL of the image (max 15 MB)
`image_base64`	No	Base64 image data (data: URI prefix allowed)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Oct 21, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does disclose useful traits: EXIF auto-rotation, the 4096px ceiling, per-call cost ($0.0045 USDC) and p99 latency. It omits whether the tool persists files or returns inline data, and no auth/rate-limit info is given, so it is strong but not complete.

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?

Front-loaded with purpose, then use cases, then a compact parameter digest, then cost/latency. Every clause earns its place and there is no filler.

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?

Given 7 parameters, 0% annotation coverage, no output schema, and thin schema descriptions, the definition supplies most of what an agent needs. The remaining gap is the return shape (base64 vs. URL vs. file reference) and the semantics of the fit modes, neither of which is recoverable elsewhere.

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 description coverage is only 29%, so the description must compensate, and it largely does: it declares that exactly one of image_base64/image_url is required (the schema's required list is empty, so this is genuinely new information), plus defaults and ranges for width, height, fit, format, and quality. It stops short of explaining what inside/cover/contain/fill actually do.

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?

States a specific verb triad (resize, crop-fit, convert) and resource (images), plus the exact supported input and output formats. An agent can distinguish this from image_alt_text, satellite_image, or screenshot 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 Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives concrete motivating scenarios: shrink screenshots before sending to a vision model, create thumbnails, or convert formats. That is clear when-to-use guidance, but it names no alternatives or exclusions (e.g., when to prefer screenshot or image_alt_text instead).

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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