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Convert an image to SVG

luw_vectorize_image

Luw.ai Vector AI: convert a photo or drawing into a clean SVG vector. Costs 1 credit.

Instructions

Luw.ai Vector AI: convert a photo or drawing into a clean SVG vector. Costs 1 credit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYesPhoto or drawing to vectorize (https:// URL, local file path, or data: URI).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.2

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds genuinely useful context by disclosing the cost ('Costs 1 credit') and the output format (SVG). However, it says nothing about how the result is obtained (immediate return vs. polling a sibling like luw_get_result) or latency, which matters for a generation tool.

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?

Two short sentences, zero filler. The action and output are front-loaded, and the cost constraint is placed last where it reads as a footnote rather than burying the purpose.

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?

For a one-parameter tool with full schema coverage and annotations covering the safety profile, the description supplies the two things structured fields cannot: the output artifact (SVG) and the credit cost. The only meaningful omission is how the converted result is retrieved, which the sibling set (luw_get_result) suggests may be asynchronous.

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% and the single parameter already documents accepted input forms (URL, local path, data URI). The description adds no parameter-level detail of its own, 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?

States a specific verb and resource ('convert a photo or drawing into a clean SVG vector'), which clearly separates it from siblings like luw_upscale_image, luw_edit_image and luw_expand_image. It also names the provider ('Luw.ai Vector AI') and the output artifact (SVG), so the agent knows exactly what this tool produces.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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

There is no when-to-use guidance beyond the implicit conversion intent, and no mention of alternatives (e.g., when to prefer luw_upscale_image or luw_edit_image). The only advisory content is the credit cost. Prerequisites and follow-up steps are absent.

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