Skip to main content
Glama

draw_image_base64

Composite an inline base64-encoded PNG onto a sprite layer at given x,y coordinates for pasting externally generated artwork.

Instructions

Composite an inline base64-encoded PNG (or other image) onto a layer at (x, y).

Useful for pasting externally generated artwork. `image_base64` may include a
`data:image/png;base64,` prefix.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
xYes
yYes
frameNo
layerNo
opacityNo
filenameYes
blend_modeNonormal
image_base64Yes
Behavior2/5

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

With no annotations, the description should disclose behavioral traits. It only mentions the optional data: prefix for the base64 string. Missing are critical details: whether the operation is destructive, what happens if the layer doesn't exist, whether it affects the undo stack, or if there are size limitations.

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?

The description is concise with two sentences, front-loading the core action. However, the extreme brevity sacrifices needed detail. One more sentence covering the filename and layer parameters would improve without losing conciseness.

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

Completeness2/5

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

Given 8 parameters, no output schema, and no annotations, the description is too sparse. It omits key parameters (filename, layer, blend_mode, etc.) and does not explain return behavior or side effects, making it incomplete for autonomous agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must explain parameters. It only clarifies x, y, and image_base64 (mentioning the prefix). The required 'filename' parameter is not explained at all, and optional parameters like opacity, blend_mode, frame, and layer receive no description, leaving their purpose ambiguous.

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 composites a base64-encoded image onto a layer at specific coordinates. The verb 'composite' is precise, and the distinction from siblings like 'import_image' (which likely uses file paths) is evident.

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 description mentions it's useful for pasting externally generated artwork, implying a use case. However, it does not provide explicit guidance on when to avoid this tool or suggest alternatives among the many sibling tools, leaving the agent to infer context.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/MalloyTheDev/aseprite-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server