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CameronFoxly

ASCII Motion MCP

by CameronFoxly

import_image

Convert image files to ASCII art on the canvas. Supports PNG, JPG, GIF, BMP with options for width, charset, color, dithering, and offset.

Instructions

Import an image file and convert it to ASCII art on the canvas. Requires optional "sharp" or "jimp" package for image processing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filePathYesPath to the image file (.png, .jpg, .gif, .bmp)
targetWidthNoTarget width in characters. If omitted, uses canvas width.
targetHeightNoTarget height in characters. If omitted, maintains aspect ratio.
charsetNoCharacters to use for brightness mapping (dark to bright) .:-=+*#%@
colorModeNoHow to apply colorsforeground
ditheringNoDithering algorithm to usenone
frameIndexNoFrame to import to (defaults to current)
offsetXNoX offset on canvas
offsetYNoY offset on canvas
Behavior2/5

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

Without annotations, the description must disclose behavior but only mentions the conversion and package dependencies. It omits critical details such as whether the canvas is cleared, how frames are handled, or error cases like missing files.

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?

The description is extremely concise: two sentences that front-load the purpose and add a dependency note. Every sentence serves a purpose with no wasted words.

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?

For a complex tool with 9 parameters and no output schema, the description is too sparse. It fails to explain workflow effects (e.g., frame creation), default behavior, or semantics like offsets, making it incomplete for optimal use.

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?

All 9 parameters have descriptions in the input schema (100% coverage), so the description adds no new meaning beyond the schema. The baseline score of 3 is appropriate.

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 it imports an image file and converts to ASCII art on the canvas. The verb 'import' and resource 'image file' are specific, and the output 'ASCII art' distinguishes it from siblings like import_ascii_text or import_video.

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?

The description provides no explicit guidance on when to use this tool versus alternatives like import_ascii_text. It only mentions package requirements, leaving the agent to infer usage from the resource type.

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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