PixelForge MCP

by mindsurf0176

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools have distinct purposes, but export_palette and extract_palette are very similar in functionality (both extract palette from a single image), which could cause confusion. The other tools are clearly differentiated by description and naming.
Naming Consistency5/5
All tool names use underscore_case and follow a verb-based pattern (e.g., pixelize, build_palette, list_motions). The naming is uniform and predictable, with no problematic mixing of styles.
Tool Count4/5
With 18 tools for pixel art creation and animation, the count is slightly above the ideal range but still reasonable. The tools cover the main workflow without being overwhelming.
Completeness5/5
The tool set covers the full pixel art pipeline: image preparation, pixelization, palette management, animation (procedural and rig-based), spritesheet packing, and batch processing. No obvious gaps for the intended domain.
Average 3.8/5 across 18 of 18 tools scored. Lowest: 3.2/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 11 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits beyond the basic operation. Missing details include whether the image is modified in-place, file format requirements beyond recommendation, and error handling behavior.
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 concise with a clear purpose sentence followed by structured argument listing. Every sentence adds value without redundancy.
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?
Given no annotations or output schema, the description is minimally adequate but lacks details on return values, preconditions (e.g., transparent background), and potential side effects. It covers the core operation but leaves gaps.
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?
With 0% schema description coverage, the description explicitly explains each parameter: src and dst as paths (PNG recommended for src), and padding as margin pixels. This adds meaningful context beyond the parameter names.
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?
The description clearly states the tool's purpose: cutting transparent margins to leave only the subject. However, it does not differentiate from sibling tools like 'remove_background' or 'batch_pixelize', which may have overlapping functionality.
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 guidance on when to use this tool versus alternatives. It lacks context about prerequisites, suitable scenarios, or when NOT to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description carries full burden. It mentions flicker prevention and shared palette but does not disclose whether the process is destructive, alters input files, or requires specific access rights. Some behavioral aspects are implied (e.g., output creation) but not explicitly stated.
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 a one-sentence purpose followed by a parameter list. It is front-loaded with the main action. No extraneous words, but the structure could be improved with section headers or clearer grouping.
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 the tool's complexity (9 parameters, 4 required, no output schema), the description is incomplete. It does not explain return values, error conditions, or side effects. The overall function is clear, but practical context for successful invocation is lacking.
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 0%, so the parameter list in the description adds value beyond the schema. It gives brief Korean descriptions for each parameter (e.g., 'frame1: second frame path (same character, different pose)' and specifies outline_style values as 'selout' or 'solid'). However, descriptions are terse and not all parameters are explained in depth.
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's purpose: pixelating two-frame animations with a common scale and shared OKLab k-means palette to prevent flickering. This specificity distinguishes it from sibling tools like pixelize (single frame) and batch_pixelize (batch).
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 implies usage for two-frame animations to avoid flickering but does not explicitly state when not to use it or mention alternatives. Siblings such as pixelize and batch_pixelize provide related but distinct functionality, but no explicit guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'OKLab perceptual distance' and 'art coherence' as behavioral traits, and explains dithering reduces banding/noise. However, it does not disclose if the tool overwrites files, required permissions, or return behavior, leaving gaps.
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 short and structured with a clear header and bullet list of parameters. Every sentence is informative without redundancy. It is front-loaded with the main purpose immediately.
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?
Given 4 parameters, no output schema, and no annotations, the description covers the core purpose and parameter meanings. However, it lacks details on output format, error handling, file overwrite behavior, and how it interacts with the filesystem, which are important for an image processing tool.
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 0%, so the description must compensate. It provides clear semantic meaning for all parameters: 'src' as input path, 'dst' as output path, 'palette' with examples and reference to 'list_palettes', and 'dither' as Floyd-Steinberg dithering. This adds significant value beyond the bare schema.
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?
The description clearly states the tool snaps an image to a palette using OKLab perceptual distance and art coherence, which is a specific verb-resource pairing. However, it does not differentiate from sibling palette tools like 'quantize_palette' or 'extract_palette', so it loses one point.
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?
No guidance on when to use this tool versus alternatives like 'quantize_palette' or 'build_palette'. The only mention is to check 'list_palettes' for palette names, which is a prerequisite, not usage context. No when-not-to-use or comparison information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose side effects and operational details. It implies a file write operation but does not explicitly state it overwrites files or requires permissions, lacking depth.
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 concise with a single sentence explaining the purpose followed by a clear list of arguments, no redundant information.
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?
The description covers inputs and output format but omits return values, error handling, and differentiation from similar sibling tools, leaving some gaps.
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?
Input schema has 0% description coverage, but the description explains each parameter's meaning (src: input image path, out: output palette path with format hint, colors: number of colors) adding value beyond the schema.
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 extracts a palette from a single image and saves it as .gpl or .hex for Aseprite import, specifying the main verb, resource, and output format.
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 guidance on when to use this tool versus alternatives like 'extract_palette' or 'build_palette', nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits like read-only, destructive side effects, or permissions. For a list tool, it is likely safe but not explicitly stated.
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 a single sentence that is direct and contains no unnecessary words. It is appropriately concise.
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?
Given the lack of an output schema, the description only vaguely states it returns a list and description. It does not specify the structure or content of each motion item, which is a gap for completeness.
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?
The tool has no parameters, so schema coverage is 100% by default. The description adds meaning by specifying that it returns a 'list and description,' which provides context beyond the schema.
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 '절차적 애니 모션 목록과 설명' translates to 'list and description of procedural animation motions,' clearly specifying the action (list) and resource (procedural animation motions). It distinguishes itself from siblings like list_palettes.
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?
No guidance is provided on when to use this tool versus alternatives such as animate or animate_rig. The description lacks any context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It mentions dst_dir is auto-created, but does not state whether the operation is read-only, if source files are modified, or side effects. For a batch mutation tool, this is insufficient.
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 structured with a Korean purpose paragraph followed by an English Args list. It is reasonably concise, though the initial sentence is somewhat long. Overall efficient with minimal redundancy.
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?
The description covers the batch nature and palette consistency, but lacks information about return values, output format, or error handling. Since no output schema exists, more detail on what the tool returns would improve completeness.
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?
With 0% schema description coverage, the description adds meaning for all 8 parameters via the Args block, e.g., clarifying that colors is used only if palette is unspecified, and explaining palette formats. This goes beyond the schema.
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 pixelizes an entire folder with uniform settings, using specific verb 'batch pixelize' and resource 'folder'. It implies distinction from sibling 'pixelize' which likely handles single images, and adds context about art consistency with palette.
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?
While the description suggests use for batch processing with uniform settings, it does not explicitly state when not to use or mention alternatives like pixelize or pixelize_pair. Usage context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It details the algorithmic steps (gamma correction, quantization, outline) and behavioral notes (e.g., indexed mode ignores upscale). This is adequate for a conversion tool, though it does not mention error conditions or performance.
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?
Purpose and algorithm are front-loaded, followed by a structured parameter list. Every sentence adds value, though the technical detail may be dense. Still efficient for the complexity.
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?
With 12 parameters, 2 required, no output schema or annotations, the description covers the tool's functionality, parameters, and key behaviors (e.g., palette types, indexed mode). Lacks usage examples or error handling but is comprehensive for a conversion tool.
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 0%, so the description must provide meaning. It does so for all 12 parameters with concise explanations (e.g., palette options, outline_style values, indexed effect). Adds significant value beyond parameter names.
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?
The description states it converts illustrations to high-quality dot sprites, which is a clear verb+resource. It is distinguishable from siblings like batch_pixelize (batch) and pixelize_pair (pair) but does not explicitly make that distinction.
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?
No guidance on when to use this tool versus alternatives (e.g., batch_pixelize, pixelize_pair). The description only explains what it does, not the context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It reveals key behaviors: flicker prevention, shared palette enforcement, output generation (spritesheet, timing JSON, GIF). It does not mention potential destructive actions (e.g., overwriting files), but the tool appears to be non-destructive (outputs to out_dir). This is adequate transparency for a creation tool.
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 well-structured with a brief intro followed by an enumerated parameter list. It is front-loaded with the core purpose. However, the parameter list is somewhat verbose (11 items) and could be more concise by grouping related parameters. Still, it is clear and usable.
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 tool with 11 parameters, no output schema, and no annotations, the description covers the main functionality, parameter roles, and output types. It mentions sprite sheet, timing JSON, and loop GIF. However, it does not describe the return value (if any) or error conditions. Overall, it is fairly complete for an animation assembly tool.
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 coverage is 0%, so description must add value. The Args section provides Korean explanations for each parameter, but they are often minimal (e.g., 'out_dir: 출력 폴더'). Some parameters like 'colors' and 'pixelize' get more meaningful descriptions. Overall, it compensates for missing schema descriptions but does not fully elaborate on parameter constraints or relationships.
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?
Description clearly states it assembles pose frames into an animation with shared palette, outputting spritesheet, timing JSON, and loop GIF. It specifies inputs (multiple frames) and processing (alignment, shared palette, flicker prevention). However, it does not explicitly distinguish itself from sibling tools like 'animate' or 'build_spritesheet', leaving some ambiguity.
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 explains the two modes (pixelize=True/False) and what they do, but it lacks explicit guidance on when to use this tool versus alternatives. For example, it doesn't state when to prefer this over 'animate' or 'batch_pixelize'. The usage context is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It explains the main action and optional swatch save, but does not describe the return value (likely a hex list), error handling, supported image formats, or any side effects beyond optional file writing. The absence of output schema exacerbates this gap.
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 concise, with a clear first-line summary, a short usage context, and a bulleted args list. Every sentence serves a purpose without redundancy.
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 simple extraction tool with 3 parameters and no output schema, the description covers basic functionality and parameter meaning. However, it is missing explicit details about the return value, input format requirements, and error states. It is adequate but not comprehensive.
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?
With 0% schema description coverage, the description compensates partially by explaining each parameter: src (input image path), colors (number of colors), and swatch (path for PNG save). However, it omits details like valid ranges for colors, default behavior (16 colors), and doesn't clarify that swatch is optional despite default null. Still, it adds meaning beyond parameter names.
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?
Description clearly states that the tool extracts a representative palette (hex list) from an image and optionally saves a swatch PNG. It distinguishes from siblings like build_palette or export_palette by specifying the image source and linking to snap_to_palette.
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?
The description explains that the extracted palette can be used as a basis for snap_to_palette to unify assets, providing a clear usage context. However, it does not explicitly mention when not to use this tool or compare it to alternatives like build_palette or quantize_palette.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the method (flood fill from four corners), the output format (RGBA PNG), and the fallback mechanism. However, since no annotations are provided, the description carries the full burden. It does not mention whether the operation is destructive, performance characteristics, or required permissions. The behavioral disclosure is adequate but not thorough.
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 exceptionally concise: one opening sentence that encapsulates the core functionality and a structured Args block. Every word contributes value, no filler. The structure front-loads the purpose and then details parameters logically.
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 the tool's moderate complexity (background removal with potential model fallback) and the absence of an output schema, the description covers the key aspects: input, output, method, and parameter roles. It lacks details on edge cases (e.g., what happens with non-solid backgrounds), but these are not necessary for typical usage. Completeness is high for the information provided.
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?
Despite 0% schema description coverage, the description's Args section adds meaningful semantics to all four parameters: src and dst are paths, tolerance is the color difference threshold (0-255), feather is alpha decay (0=sharp, 1=fully transparent). This compensates significantly for the schema's lack of descriptions, providing clear meaning beyond names and types.
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's purpose: removing solid or off-white backgrounds via four-corner flood fill with a fallback to a background removal model. It uses a specific verb ('transparentize' implied) and resource ('background'), and is clearly distinct from sibling tools like pixelize or autocrop.
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?
No explicit guidance is provided on when to use this tool versus alternatives. The description mentions a fallback to a background removal model, but does not specify when the flood fill fails or how to decide between this tool and other background removal methods. There are no 'when not to use' statements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses the output (rig files to disk) and that it's a template editable later. However, it omits details like overwrite behavior, required permissions, or side effects, which are important for a file-writing operation.
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?
Description is short, front-loaded with the main action, and uses a structured Args section. It is efficient but could be slightly more polished (e.g., removing redundancy).
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 simple tool with one parameter and no output schema, the description covers purpose, composition, and usage context. It provides enough detail for the agent to understand the tool's role without being overly verbose.
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?
The only parameter 'out_dir' is explained as 'folder to save rig', which adds meaningful context beyond the schema's 'Out Dir' label. With low schema coverage (0%), the description adequately compensates by clarifying the parameter's role.
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?
Description clearly states the tool saves a built-in biped character rig to disk, specifying the resource (built-in rig with parts, skeleton, clips) and action (save). It distinguishes from siblings like export_rig_kit by framing it as a starting template, which no other sibling does.
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?
Description indicates it's a starting template for user rig authoring and demos, implying use for initial setup. However, it does not explicitly state when to use this tool over alternatives (e.g., assembling an animation or exporting a custom rig) or provide exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It discloses that the tool exports files and that the outputs are intended for further use, but it does not mention permissions, overwrite behavior, or potential side effects. Some behavioral traits are implied but not detailed.
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 detailed but well-structured with a clear first sentence, bullet points for outputs, and an Args section. It is somewhat lengthy but every sentence adds value. Could be slightly more concise, but it is not wasteful.
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 the lack of annotations and output schema, the description covers the tool's purpose, output contents, parameters, and workflow integration. It is nearly complete for a tool of this complexity, though missing details on error handling or directory overwrite behavior.
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?
The input schema has 0% description coverage, but the description compensates by explaining each parameter: out_dir (folder), character (description for prompt), kind (rig type with options humanoid or biped). This adds significant meaning beyond the raw JSON schema, though defaults and constraints on out_dir are not elaborated.
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 saves a rig kit for sprite creation, lists output files (rig.json, PNGs, layout_guide.png, prompts.md, README), and explains its role in the workflow. It effectively distinguishes from sibling tools by mentioning that animate_rig uses the output.
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 implies the tool is for creating a new rig kit from scratch and that the output is used by animate_rig, but it does not explicitly state when to use this tool versus alternatives like assemble_animation or other sibling tools. The guidance is indirect.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses outputs (PNG frames, spritesheet, timing JSON, GIF) and explains the 'pixelize_first' workflow. However, it does not mention error conditions, performance considerations, or permission requirements.
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 well-structured with a clear purpose, output list, and argument list. It is concise and front-loaded, but the argument list could be slightly trimmed if redundant with schema.
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?
Given 14 parameters, 2 required, and no output schema, the description covers core behavior and output formats. However, it lacks explicit links to sibling tools (e.g., when to use 'list_motions' for valid motion values) and does not detail the output JSON structure or spritesheet layout.
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 0%, but the description lists each argument with brief explanations (e.g., 'motion: breathe/bob/float..., amplitude: motion strength in px'). This adds meaning beyond the schema's raw keys and defaults, though some parameter details remain implied (e.g., 'out_dir' auto-created).
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 automatically generates procedural loop animation from a static image without additional art, listing outputs and key parameters. It distinguishes from sibling tools like 'animate_rig' by implying this tool works directly on images.
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 'pixelize_first' for converting illustrations before rigging, but does not explicitly state when to use this tool versus siblings like 'animate_rig' or 'batch_pixelize'. Usage context is implied but not directed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions that resolution is maintained and colors are reduced, which implies a non-destructive transformation. However, it does not disclose any side effects, required permissions, or handling of file formats, leaving gaps in behavioral transparency.
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: one Korean sentence stating the main purpose followed by bullet points for parameters. There is no wasted text, and the key information is front-loaded. Every sentence serves a purpose.
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?
Given 4 parameters, no output schema, and no annotations, the description should ideally cover return values and potential limitations. It explains parameters but does not state what the tool returns (e.g., success indicator or output path) or any constraints (e.g., image format support). This leaves some context gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the schema has 0% description coverage, the tool description includes an 'Args' section that explains each parameter in natural language (e.g., 'input image path', 'target color count'). This adds significant meaning beyond the schema's type/title information, fully compensating for the lack of schema descriptions.
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 that the tool reduces the number of colors while preserving resolution, which is a specific verb+resource combination. It distinguishes from siblings like pixelize (resolution reduction) and build_palette (creating palettes), as it explicitly mentions 'resolution maintenance' and 'palette unification'.
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 implies use cases (reducing colors for palette unification or capacity saving) but does not explicitly guide when to use this tool over alternatives like extract_palette or snap_to_palette. It lacks explicit 'when-to-use' or 'when-not-to-use' guidance, which is important given the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that columns=0 means horizontal layout and that metadata is written optionally, but does not discuss side effects like overwriting dst or image format restrictions.
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?
Description is extremely concise, with a single sentence for the main purpose followed by a bullet-like list of arguments. No redundant words, front-loaded with the key action.
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 no output schema and 5 parameters, the description covers all parameters and main behavior. Missing details on error handling, supported image formats, or performance implications, but sufficient for a straightforward packing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds clear meaning for all 5 parameters: frames (list ordered), dst (output path), columns (grid columns), cell_padding (inner padding), write_metadata (save JSON). It compensates fully for the schema gap.
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?
Description clearly states the tool packs multiple frames into a uniform grid spritesheet with JSON metadata. It uses specific verbs ('pack') and resources ('spritesheet'), and distinguishes from sibling tools like animate or autocrop.
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 for engine importing but does not explicitly state when to use this tool versus alternatives like animate or pixelize. No guidance on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description details the animation process (attaching parts to bones, keyframing, compositing) and outputs, clarifying it is 'real animation' not procedural. With no annotations provided, this disclosure is valuable, though it omits potential side effects or resource requirements.
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 well-structured with a concise first paragraph explaining the concept, followed by a bullet list of outputs and then parameter descriptions. It is slightly long but front-loaded and organized, making it easy to parse.
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 tool with 9 parameters, no output schema, and no annotations, the description is quite complete: it explains the process, outputs, and every parameter. However, it lacks information on return values or error handling, which would be helpful for full contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides comprehensive explanations for all 9 parameters in the 'Args' section, including allowed values (e.g., 'humanoid' for rig, default clip 'walk'). Since schema coverage is 0%, this adds critical meaning beyond the schema's titles and defaults.
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's function: rendering frame-by-frame pose animation using a cutout skeletal rig, producing individual PNGs, spritesheet, timing JSON, and loop GIF. It distinguishes from procedural warp, making the purpose unambiguous.
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 built-in rigs (humanoid, biped) and their animations, implying use cases, but does not explicitly state when to use this tool versus siblings like 'animate' or 'assemble_animation'. Usage guidance is only implicit via the parameter details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly indicates the tool is read-only (list operation) and returns specific data (list and count). No mention of permissions or side effects, but for a simple list tool this is sufficient.
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 a single sentence that efficiently conveys the tool's purpose without any filler words.
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?
The description explains the return value (list and color count) but does not detail the format or structure. Given no output schema, this is adequate for a simple list tool, but could be more complete.
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?
There are no parameters, and schema description coverage is 100%. The description adds no parameter details because none are needed. Baseline for 0 parameters is 4.
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 that the tool returns the list of built-in curated palettes and the color count per palette (specific verb+resource). It is distinct from sibling tools like build_palette, export_palette, etc., which involve creation or modification.
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 implies the tool is for listing built-in palettes, but does not explicitly state when to use it versus alternatives (e.g., snap_to_palette). No when-not guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions 'locked common palette' and OKLab k-means, but lacks details on side effects, permission requirements, or idempotency. Adequate but could be more transparent.
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 efficient sentences for purpose and usage, followed by a structured Args list. No redundant information. Front-loaded with the main action, making it quick to parse.
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?
The description covers parameters, output format, and downstream use. However, it lacks information on the return value (if any) since there is no output schema. Still, for a file-saving tool, the omission is minor and the description is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, but the description's Args section explains all four parameters with clear purposes: sources (reference paths), out (save path with format), colors (number of colors), swatch (optional PNG output). This adds significant value beyond the schema.
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 creates a locked common palette from multiple references using OKLab k-means and saves as .gpl/.hex. It distinguishes from siblings like extract_palette (single reference) and quantize_palette (existing palette) by specifying the multi-reference input and algorithm.
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?
It explicitly guides the user to pass the resulting palette to pixelize/batch_pixelize for unifying assets. However, it does not compare with alternatives like extract_palette or snap_to_palette, nor does it state when not to use this tool.
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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