PixelPanda MCP Server

Server Quality Checklist

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Latest release: v0.1.2
Disambiguation4/5
Most tools have distinct purposes, but some overlap exists. For example, 'enhance_image' and 'upscale_image' both involve AI-based image improvement, which could cause confusion. However, descriptions clarify that 'enhance_image' focuses on restoration and sharpening, while 'upscale_image' is for resolution increase. Other tools like 'adjust_image' and 'enhance_image' also share some functional overlap but are differentiated by method (manual vs. AI).
Naming Consistency5/5
Tool names follow a highly consistent verb_noun pattern throughout, such as 'add_border', 'adjust_image', 'analyze_image', etc. All tools use snake_case and descriptive verbs that clearly indicate the action, making the set predictable and easy to navigate. There are no deviations in naming conventions.
Tool Count3/5
With 32 tools, the count feels heavy for an image processing server, though not extreme. It covers a broad range of operations from basic edits to AI generation, but some tools might be redundant or overly specialized. A more streamlined set of 15-25 tools could improve coherence without losing functionality.
Completeness5/5
The tool set provides comprehensive coverage for image processing and AI generation. It includes basic operations (crop, resize, convert), advanced edits (blur, watermark, transparency), AI features (enhance, upscale, background removal), and product photo generation workflows (with supporting tools like list_avatars and upload_product). There are no obvious gaps; agents can perform end-to-end tasks without dead ends.
Average 3.6/5 across 32 of 32 tools scored. Lowest: 2.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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.
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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, so the description carries the full burden of behavioral disclosure. It mentions cost ('1 credit per image') and authentication ('Requires PIXELPANDA_API_TOKEN'), which adds some context beyond basic functionality. However, it fails to disclose critical behavioral traits such as whether the operation is read-only or destructive, expected response format, error handling, rate limits, or job processing details (e.g., asynchronous vs. synchronous). For a generative AI tool with no annotation coverage, 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 appropriately sized and front-loaded: the first sentence clearly states the purpose, followed by cost and authentication details in separate lines. It avoids unnecessary fluff and uses bullet-like formatting for key points. However, the structure could be slightly improved by integrating the cost and authentication into a more cohesive paragraph, but it remains efficient with zero waste.
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 complexity of an AI generation tool with 4 parameters, 0% schema coverage, no annotations, but an output schema present, the description is moderately complete. It covers purpose, cost, and authentication but lacks parameter explanations, behavioral details, and usage context. The output schema may handle return values, reducing the burden, but overall, it's adequate with clear gaps, especially in parameter semantics and sibling differentiation.
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 description coverage is 0%, so the description must compensate for undocumented parameters. It does not explain any of the 4 parameters (avatar_uuid, product_uuid, num_outputs, prompt) beyond what the schema provides (only titles and types). No additional meaning, usage examples, or constraints are given, such as what avatars or products are valid, how num_outputs affects results, or how the prompt influences generation. This leaves parameters largely ambiguous.
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: 'Generate AI try-on photos with an avatar wearing your product (clothing).' It specifies the verb ('Generate'), resource ('AI try-on photos'), and scope ('with an avatar wearing your product'), which is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'generate_product_photo' or 'generate_scenes', which might also involve image generation, so it falls short of a perfect score.
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 minimal usage guidance: it mentions '1 credit per image' and 'Requires PIXELPANDA_API_TOKEN,' which hints at cost and authentication prerequisites. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'generate_product_photo' or 'generate_scenes'), no mention of when not to use it, and no clear context for selection among siblings. This leaves gaps in practical application.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the API token requirement, which is useful context about authentication needs. However, it doesn't describe what 'saved products' means, whether results are paginated, what format they're returned in, or any rate limits—significant gaps for a listing 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 appropriately sized with two sentences that each serve a purpose: stating the tool's function and noting the authentication requirement. It's front-loaded with the core purpose. However, it could be slightly more structured by separating the requirement into a distinct note.
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 that there's an output schema (which handles return values), no annotations, and low complexity, the description is somewhat complete but has gaps. It covers authentication and the basic purpose but misses parameter details and behavioral context like filtering or result format, making it adequate but not fully helpful.
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?
The schema description coverage is 0%, so the description must compensate. It doesn't mention the 'category' parameter at all, leaving it completely undocumented. Since there's only one parameter and it's optional, the baseline is 4, but the failure to address it reduces the score to 3.
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 verb ('List') and resource ('your saved products in PixelPanda'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_avatars' or 'list_jobs' beyond the resource name, which is why it doesn't reach a perfect score.
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 mentions an API token requirement, but this is a prerequisite rather than usage context. There's no indication of when to prefer this over other listing tools or when it's appropriate to use.
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?
With no annotations provided, the description carries full burden. It discloses that the tool 'runs locally' and is 'free' with 'no account needed', which are useful behavioral traits. However, it doesn't mention performance characteristics, file format support, error conditions, or what happens when output_path is null.
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 with only two sentences that both earn their place. The first sentence states the core functionality, and the second provides important accessibility information. No wasted words or unnecessary elaboration.
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 an image processing tool with 3 parameters, 0% schema coverage, no annotations, but with an output schema, the description is incomplete. While the output schema may cover return values, the description lacks crucial information about parameter meanings, file format support, and behavioral constraints that would help an agent use this tool effectively.
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?
With 0% schema description coverage and 3 parameters, the description provides no information about any parameters. It doesn't explain what 'radius' controls, what formats 'file_path' accepts, or what happens when 'output_path' is null versus specified. The description fails to compensate for the complete lack of schema documentation.
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 action ('Apply Gaussian blur') and resource ('to an image'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'pixelate_image' or 'grayscale_image', but the specific blur technique mentioned provides some 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?
The description provides no guidance on when to use this tool versus alternatives like 'pixelate_image' or 'grayscale_image' for similar image modification purposes. It mentions it's 'Free tool — runs locally, no account needed' which indicates accessibility but doesn't help with tool selection decisions.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context: 'Free tool — runs locally, no account needed' explains cost, execution environment, and authentication requirements. However, it doesn't mention whether the operation is destructive to the original file, what happens with output paths, or any rate limits.
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 and well-structured: first sentence states purpose and key parameters, second sentence provides important behavioral context. Every sentence earns its place with zero wasted words.
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 that there's an output schema (which handles return values), no annotations, and moderate complexity, the description is somewhat complete but has gaps. It covers the basic purpose and some behavioral context but lacks parameter explanations and usage guidelines relative to siblings.
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 description coverage is 0%, so the description must compensate for undocumented parameters. It mentions output formats ('jpeg, webp, or png') which helps clarify the output_format parameter, but doesn't explain file_path, quality, or output_path semantics. With 4 parameters and only partial coverage, this is inadequate.
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: 'Compress an image by reducing quality.' It specifies the action (compress) and resource (image), distinguishing it from siblings like resize_image or convert_format. However, it doesn't explicitly differentiate from adjust_image or enhance_image, which might also affect quality.
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. With siblings like adjust_image, convert_format, and resize_image that might serve overlapping purposes, there's no indication of when compression is preferred over other image manipulation methods.
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?
With no annotations provided, the description carries the full burden. It discloses that the tool runs locally and requires no account, which is useful behavioral context. However, it lacks details on performance, error handling, or output behavior, leaving gaps in understanding how the tool operates beyond basic functionality.
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 and front-loaded, with the core purpose stated first and additional context in a brief second sentence. Every sentence adds value without any wasted words, making it highly efficient for quick understanding.
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 tool's low complexity (simple image transformation) and the presence of an output schema (which handles return values), the description is somewhat complete. However, with no annotations and 0% schema coverage, it lacks details on parameters and deeper behavioral traits, making it only minimally adequate.
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 description coverage is 0%, so the description must compensate for undocumented parameters. It adds no information about the two parameters (file_path and output_path), such as their roles, formats, or constraints. This fails to provide meaningful semantics beyond what the bare schema indicates.
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 with a specific verb ('convert') and resource ('image'), and distinguishes it from siblings by specifying the transformation to grayscale. However, it doesn't explicitly differentiate from similar tools like 'adjust_image' or 'invert_image' beyond the grayscale aspect, which prevents a perfect score.
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 'adjust_image' or 'invert_image', nor does it mention prerequisites or exclusions. The only contextual note is about it being free and local, which doesn't help in tool selection among siblings.
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?
With no annotations provided, the description carries the full burden. It discloses that the tool is 'Free — runs locally, no account needed,' which adds useful context about cost and execution environment. However, it lacks details on side effects (e.g., file overwriting), error handling, or performance limits, leaving behavioral gaps.
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 with zero waste. The first sentence states the purpose, and the second adds valuable operational context. Every word earns its place, making it easy to scan and understand quickly.
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, 0% schema coverage, but an output schema exists, the description is moderately complete. It covers the core action and tool context but misses parameter details and behavioral specifics. The output schema mitigates some gaps, but overall it's adequate with clear room for improvement.
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 description coverage is 0%, so the description must compensate. It mentions 'pixel block size' (mapping to pixel_size) but doesn't explain file_path or output_path parameters. With 3 parameters total and only one vaguely addressed, this is insufficient for effective use.
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 action ('Pixelate an image') and specifies the key parameter ('with a given pixel block size'), which distinguishes it from siblings like blur_image or grayscale_image. However, it doesn't explicitly contrast with all similar tools (e.g., blur_image might have overlapping effects), keeping it from a perfect score.
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 blur_image or adjust_image, nor does it mention prerequisites or exclusions. The note about being a free local tool is helpful but doesn't address tool selection among siblings.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds some context: 'Expands canvas by default' clarifies a default behavior, and 'Free tool — runs locally, no account needed' informs about cost and execution environment. However, it doesn't cover critical aspects like whether the operation is destructive (modifies the original file), error conditions, or performance characteristics.
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 and well-structured: the first sentence states the core functionality with key details, the second adds behavioral context, and the third provides execution context. Every sentence earns its place with no wasted words, and information is front-loaded appropriately.
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 tool's moderate complexity (image transformation with 4 parameters), no annotations, and an output schema (which handles return values), the description is partially complete. It covers the basic operation and some behavioral context but lacks parameter explanations and usage guidance. The presence of an output schema means return values don't need description, but other gaps remain.
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 description coverage is 0%, so the description must compensate for undocumented parameters. It only mentions 'degrees' (counter-clockwise rotation) and implies 'expand' (canvas expansion default), but doesn't explain 'file_path' (input image location) or 'output_path' (where to save the result). With 4 parameters and low coverage, this leaves significant gaps in understanding parameter roles.
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: 'Rotate an image by the specified degrees (counter-clockwise).' It specifies the action (rotate), resource (image), and direction (counter-clockwise). However, it doesn't explicitly differentiate from sibling tools like 'flip_image' or 'adjust_image' which might also involve image orientation changes.
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 doesn't mention sibling tools like 'flip_image' (for mirroring) or 'adjust_image' (which might include rotation among other adjustments), nor does it specify prerequisites or exclusions. The 'Free tool — runs locally, no account needed' line is useful context but doesn't address tool selection.
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?
With no annotations provided, the description carries full burden. It mentions an authentication requirement ('Requires PIXELPANDA_API_TOKEN'), which is useful. However, it doesn't disclose other behavioral traits like rate limits, whether the upload is destructive to existing data, error handling, or what happens after upload (e.g., job creation). For a mutation tool with zero annotation coverage, this is inadequate.
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 front-loaded with the core purpose in the first sentence, followed by essential details in two concise sentences. Every sentence adds value (authentication requirement, category options), with zero waste or redundancy. It's appropriately sized for the tool's complexity.
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, 0% schema coverage, and an output schema present (which reduces need to explain return values), the description is moderately complete. It covers authentication and category semantics, but lacks details on file requirements, error cases, or integration with sibling tools. For a mutation tool, this leaves gaps, making it minimally adequate.
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 adds significant value by explaining the 'category' parameter with a list of allowed values (clothing, accessories, etc.), which isn't in the schema. However, it doesn't clarify 'file_path' (e.g., format, size limits) or 'name' (e.g., optional naming), leaving some gaps. Since it compensates partially but not fully, a 4 is appropriate.
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 verb ('upload') and resource ('product image'), and specifies the target service ('PixelPanda') and purpose ('for use in AI photo generation'). However, it doesn't explicitly differentiate from sibling tools like 'generate_product_photo' or 'list_products', which would require a 5.
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 mentions a prerequisite ('Requires PIXELPANDA_API_TOKEN') but provides no guidance on when to use this tool versus alternatives like 'generate_product_photo' or 'list_products'. There's no explicit when/when-not context or named alternatives, leaving usage unclear.
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 discloses key behavioral traits: the tool is free, runs locally, and requires no account, which adds useful context about accessibility and execution environment. However, it doesn't cover other important aspects like performance (e.g., speed, resource usage), error handling, or what happens with the output (e.g., file overwriting, format-specific limitations). The description doesn't contradict any annotations, as there are none.
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 appropriately sized and front-loaded: the first sentence states the core purpose, and the second adds crucial behavioral context. Every sentence earns its place with no wasted words, making it easy to scan and understand quickly.
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 tool's moderate complexity (image conversion with 3 parameters), no annotations, and an output schema present (which likely covers return values), the description is partially complete. It covers the purpose and some behavioral traits but lacks details on parameter semantics and usage nuances. With the output schema handling return values, the description doesn't need to explain outputs, but it should do more to address input parameters and tool-specific behaviors.
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?
The schema description coverage is 0%, meaning none of the parameters (file_path, target_format, output_path) are documented in the schema. The description lists target formats but doesn't explain the parameters' meanings, such as what file_path expects (e.g., local path, URL), how target_format interacts with the listed formats, or what output_path does (e.g., default behavior, null handling). It adds minimal value beyond the schema, failing to compensate for the low coverage.
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: converting images between specified formats (png, jpeg, webp, bmp, tiff). It uses the specific verb 'convert' with the resource 'image' and lists the supported formats. However, it doesn't explicitly differentiate from sibling tools like 'compress_image' or 'resize_image' that also transform images but for different purposes.
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 context by mentioning it's a 'Free tool — runs locally, no account needed,' which suggests when to use this tool (for local, no-account conversions). However, it doesn't provide explicit guidance on when to choose this over alternatives like 'compress_image' for format changes with compression or other image manipulation siblings, nor does it state any exclusions or prerequisites beyond the implied local operation.
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?
With no annotations provided, the description carries the full burden. It discloses cost ('1 credit per scene') and authentication needs ('Requires PIXELPANDA_API_TOKEN'), which are valuable behavioral traits. However, it misses details like rate limits, response format, or whether it's an async operation (though output schema might cover this), leaving gaps in 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 front-loaded with the core purpose, followed by key constraints and requirements in two short sentences. Every sentence adds value: the first defines the tool, the second covers cost and authentication. There is no wasted text, making it highly efficient.
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, 0% schema coverage, but an output schema exists, the description is partially complete. It covers purpose, cost, and auth needs, but lacks parameter explanations and behavioral details like error handling. The output schema may help with return values, but overall completeness is moderate for a tool with multiple parameters and no annotation support.
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 description coverage is 0%, so the description must compensate. It provides no information about the three parameters (product_uuid, num_scenes, category), such as what a product_uuid is, how num_scenes relates to credits, or what categories are available. This leaves parameters largely unexplained beyond the 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 verb 'Generate' and the resource 'AI product scene photos', specifying the types (lifestyle, studio, detail shots) and excluding avatars. It distinguishes from sibling tools like 'generate_product_photo' by focusing on scenes rather than single photos, but doesn't explicitly contrast with all siblings.
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 generating product scenes and mentions 'No avatar needed', which suggests when not to use it (if avatars are required). However, it lacks explicit guidance on when to choose this over alternatives like 'generate_product_photo' or other image tools, and doesn't mention prerequisites beyond the API token.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the API token requirement, which is useful context for authentication. However, it lacks details on rate limits, pagination, error handling, or what 'recent' means, leaving gaps in behavioral understanding.
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 with two short sentences that directly state the purpose and a key requirement. There is no wasted text, and it is front-loaded with the core functionality, making it efficient and well-structured.
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 tool's low complexity (one parameter) and the presence of an output schema, the description is somewhat complete but lacks depth. It covers authentication but misses details on parameter usage, behavioral traits, and differentiation from siblings, making it adequate but with clear gaps.
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 description must compensate for the undocumented parameter 'limit'. The description adds no information about parameters, failing to explain what 'limit' controls or its semantics. Baseline is 3 due to only one parameter, but the description doesn't enhance understanding beyond the 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 verb ('List') and resource ('your recent AI generation jobs'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'check_job_status' or 'list_avatars', which prevents a perfect score.
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 'check_job_status' or 'list_products'. It mentions an API token requirement, but this is a prerequisite rather than usage context, so it falls short of providing meaningful selection criteria.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context: the tool is free, runs locally, and requires no account, which informs about cost, execution environment, and authentication needs. However, it doesn't cover other behavioral traits like performance, error handling, or output specifics (e.g., file format, quality). The description partially compensates for the lack of annotations but leaves gaps.
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 and front-loaded: the first sentence states the core purpose, and the second adds critical behavioral context. Every sentence earns its place with no wasted words, making it easy to scan and understand quickly. The structure is efficient and well-organized.
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 tool's moderate complexity (image merging with 4 parameters), no annotations, 0% schema coverage, but an output schema exists, the description is partially complete. It covers the basic purpose and some behavioral context but lacks details on parameters, error cases, or output specifics. The output schema likely handles return values, but the description doesn't fully compensate for the missing annotation and schema information, leaving room for improvement.
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 description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'Direction: horizontal, vertical, or grid,' which adds meaning for the 'direction' parameter beyond the schema. However, it doesn't explain 'file_paths' (e.g., supported formats), 'gap' (e.g., units or constraints), or 'output_path' (e.g., default behavior). With 4 parameters and low schema coverage, the description provides only partial semantic clarification.
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: 'Merge multiple images into one' with specific direction options (horizontal, vertical, or grid). This is a clear verb+resource statement, though it doesn't explicitly differentiate from sibling tools like 'combine_images' if such existed. The purpose is specific and actionable.
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 provides some usage context by mentioning it's a 'Free tool — runs locally, no account needed,' which implies when to use it (for local processing without authentication). However, it doesn't explicitly state when to choose this tool over alternatives like 'combine_images' or other image manipulation siblings, nor does it mention prerequisites or exclusions. The guidance is implied rather than explicit.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds context about being free, local, and not requiring an account, which is helpful for understanding operational constraints. However, it lacks details on side effects (e.g., file overwriting), error handling, or output specifics, leaving gaps for a mutation 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?
The description is extremely concise with two sentences that are front-loaded: the first states the core purpose, and the second adds operational context. Every word earns its place, with no redundancy or unnecessary elaboration.
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 tool's moderate complexity (image mutation with 4 parameters), no annotations, and an output schema (which reduces need to describe returns), the description is incomplete. It covers purpose and basic operational context but misses parameter guidance and detailed behavioral traits, making it adequate but with clear gaps.
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 description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'solid color border' which hints at 'color' and 'width' parameters, but doesn't explain 'file_path' or 'output_path' semantics, nor provide format details. This partial coverage is insufficient given the 4 parameters.
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 specific action ('Add a solid color border') and resource ('around an image'), distinguishing it from sibling tools like 'crop_image', 'resize_image', or 'round_corners' that modify images differently. It precisely defines the tool's function without being vague or tautological.
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 'round_corners' or 'adjust_image', nor does it mention prerequisites or exclusions. It only states it's a 'Free tool — runs locally, no account needed,' which is useful but doesn't address tool selection context.
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 discloses key behavioral traits: it's free, runs locally, and requires no account, which helps the agent understand cost, execution environment, and authentication needs. However, it lacks details on rate limits, error handling, or what happens if the input image is invalid, leaving gaps in behavioral context.
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 appropriately sized and front-loaded: the first sentence states the core purpose, the second adds shape details, and the third provides behavioral context. Every sentence earns its place with no wasted words, making it efficient and 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?
Given the tool's moderate complexity (4 parameters, no annotations, but has an output schema), the description is reasonably complete. It covers purpose, shape options, and key behavioral traits (free, local, no account). Since an output schema exists, it doesn't need to explain return values. However, it could better address parameter semantics and usage guidelines to be fully comprehensive.
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 description coverage is 0%, so the description must compensate for undocumented parameters. It mentions shape options (circle, square, or rounded), which adds meaning beyond the schema's generic 'shape' parameter. However, it doesn't explain the other three parameters (file_path, size, output_path), leaving their semantics unclear. With 4 parameters and only one partially covered, this is insufficient.
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: 'Create a profile picture from an image' with specific shape options (circle, square, or rounded). It uses a specific verb ('create') and resource ('profile picture'), distinguishing it from siblings like 'add_border' or 'crop_image' which modify images differently. However, it doesn't explicitly differentiate from 'round_corners' which might 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by mentioning it's a 'Free tool — runs locally, no account needed,' suggesting it's suitable for local processing without authentication. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'round_corners' or 'crop_image' for similar tasks, 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that it's a free tool that runs locally with no account needed, which adds useful behavioral context about accessibility and execution environment. However, it doesn't cover aspects like whether the original file is modified, error handling, or performance characteristics.
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 with just two sentences that each add distinct value. The first sentence explains the core functionality, and the second provides important behavioral context. No wasted words or 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?
Given that there's an output schema (which handles return values), no annotations, and 6 parameters with 0% schema coverage, the description provides basic purpose and some behavioral context but lacks parameter details for half the inputs and doesn't help differentiate from sibling tools. It's minimally adequate but has clear gaps.
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 description coverage is 0%, so the description must compensate. It explains that parameters represent rectangle coordinates (left, top, right, bottom in pixels), which clarifies the meaning of 4 out of 6 parameters. However, it doesn't address 'file_path' or 'output_path' semantics, leaving significant gaps in parameter understanding.
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 specific action ('Crop an image') and the resource ('image'), specifying the rectangle parameters in pixels. It distinguishes from siblings like 'resize_image' or 'adjust_image' by focusing on cropping rather than resizing or other adjustments.
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 'resize_image' or 'adjust_image' from the sibling list. It mentions it's a free local tool, but this doesn't help differentiate usage scenarios.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions an authentication requirement ('Requires PIXELPANDA_API_TOKEN'), which is useful context, but it doesn't describe other behavioral traits like rate limits, pagination, or what happens if no avatars exist. This is a minimal but adequate disclosure given the lack of annotations.
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 short sentences that each serve a clear purpose: stating the tool's function and noting an authentication requirement. It's front-loaded with the main purpose. A point is deducted because the second sentence could be integrated more smoothly, but overall it's efficient.
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 low complexity (0 parameters, no annotations, but has an output schema), the description is reasonably complete. It covers the purpose and authentication need, and since an output schema exists, it doesn't need to explain return values. However, it could benefit from more behavioral context (e.g., response format hints) to achieve a perfect score.
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 0 parameters, and the schema description coverage is 100%, so no parameter information is needed. The description appropriately doesn't discuss parameters, earning a baseline score of 4 for not adding unnecessary details.
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 with a specific verb ('List') and resource ('your saved AI avatars'), and provides context about their use ('for use in product photo generation'). However, it doesn't distinguish this tool from its siblings (like 'list_jobs' or 'list_products'), which would require a 5.
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 includes a prerequisite ('Requires PIXELPANDA_API_TOKEN'), which provides some usage context, but it doesn't offer guidance on when to use this tool versus alternatives (e.g., compared to 'list_jobs' or 'list_products') or any explicit exclusions. This leaves gaps in usage guidance.
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?
With no annotations provided, the description carries full burden. It discloses that it's a 'Free tool — runs locally, no account needed' which is valuable behavioral context about cost, execution environment, and authentication requirements. However, it doesn't mention whether the operation modifies the original file or creates a new one, what happens with invalid opacity values, or any rate limits. The description adds some context but leaves important behavioral aspects unspecified.
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 perfectly concise with two sentences that each earn their place. First sentence defines core functionality with precise numeric context. Second sentence provides important behavioral context about cost and execution. No wasted words, well-structured, and front-loaded with the most important information.
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 3 parameters with 0% schema coverage and no annotations, the description does reasonably well. It explains the most critical parameter (opacity) thoroughly and provides valuable behavioral context about being free/local. With an output schema present, it doesn't need to explain return values. However, it could better explain file_path and output_path semantics for a tool that modifies files.
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 description must compensate. It explains the 'opacity' parameter's meaning and valid range (0.0-1.0), which adds crucial semantics beyond the schema's bare type definition. However, it doesn't explain 'file_path' (input image location) or 'output_path' (where to save result, with null default meaning what?). The description partially compensates but leaves two of three parameters inadequately explained.
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: 'Adjust the opacity/transparency of an image' with specific numeric ranges (0.0-1.0). It distinguishes from siblings like 'adjust_image' by focusing specifically on transparency rather than general adjustments. However, it doesn't explicitly contrast with 'grayscale_image' or 'invert_image' which also modify image appearance.
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 'adjust_image' (which might include opacity adjustments) or other image modification tools. It mentions 'Free tool — runs locally, no account needed' which indicates accessibility but doesn't help choose between similar tools. No explicit when/when-not statements or alternative recommendations are 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?
With no annotations provided, the description carries the full burden. It discloses that the tool runs locally and requires no account, adding useful behavioral context. However, it doesn't cover aspects like whether the original image is modified or a new file is created, error handling, or performance limits, leaving gaps in 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 front-loaded with the core purpose, followed by key details (position options and tool characteristics). Both sentences earn their place by providing essential information without redundancy, making it highly efficient and well-structured.
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 complexity (6 parameters, no annotations, but has an output schema), the description is moderately complete. It covers the basic purpose and some behavioral traits, but lacks parameter explanations and detailed usage scenarios. The output schema might handle return values, but the description doesn't fully compensate for the missing annotations and low schema coverage.
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 description coverage is 0%, so the description must compensate. It mentions 'Position: center, bottom-right, or tiled', which clarifies one parameter (position), but doesn't explain the other 5 parameters (e.g., file_path, text, opacity). This partial coverage is insufficient given the low schema support.
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 specific action ('Add a text watermark') and resource ('to an image'), distinguishing it from sibling tools like 'add_border' or 'remove_text'. It specifies the type of watermark (text-based) and mentions position options, 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 implies usage context by stating it's a 'Free tool — runs locally, no account needed', which suggests when to use it (for local, account-free processing). However, it doesn't explicitly differentiate when to choose this over alternatives like 'add_border' or provide exclusions, leaving some ambiguity.
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 and adds valuable behavioral context: it explains the numeric scale (1.0 = no change), indicates it's a free tool that runs locally without an account, and implies it performs image processing. However, it doesn't detail side effects like file overwriting or performance characteristics.
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 sentences, zero waste: the first explains the core function and parameter semantics, the second adds important behavioral context about cost and execution. It's appropriately sized and front-loaded with the essential information.
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 6 parameters with 0% schema coverage and no annotations, the description does well by explaining 4 parameters and key behavioral traits. With an output schema present, it doesn't need to explain return values. However, it misses details on 'file_path' and 'output_path' usage, and lacks sibling differentiation.
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 explains the meaning of adjustment parameters (brightness, contrast, sharpness, saturation) and their numeric scale, which adds crucial semantics beyond the schema's titles. It doesn't cover 'file_path' or 'output_path', leaving some parameters undocumented.
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 adjusts brightness, contrast, sharpness, and saturation of an image, which is a specific verb+resource combination. It distinguishes from siblings like 'enhance_image' or 'grayscale_image' by specifying the exact adjustments, though it doesn't explicitly contrast with them.
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 like 'enhance_image' or 'blur_image'. The description mentions it's a free local tool, which hints at cost/access context, but doesn't specify use cases or exclusions relative to sibling tools.
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 discloses key behavioral traits: it's a 'Free tool' with rate limits ('3 uses/day without an account') and authentication requirements ('Unlimited with a PixelPanda API token'). This covers usage constraints and auth needs, though it doesn't detail output format, error handling, or specific AI model 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 highly concise and well-structured: two sentences that efficiently convey the tool's purpose, capabilities, and usage constraints. Every sentence adds value—the first explains what the tool does, and the second covers rate limits and authentication—with no wasted words or 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?
Given the tool's moderate complexity (AI analysis with rate limits), no annotations, and an output schema exists (which handles return values), the description is fairly complete. It covers purpose, capabilities, and behavioral constraints like rate limits and auth. However, it lacks details on error cases, input file requirements (e.g., format, size), or how the analysis results are structured, leaving some gaps for an AI agent.
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?
The input schema has 1 parameter ('file_path') with 0% description coverage, meaning the schema provides no semantic details. The description adds no parameter-specific information beyond the tool's overall purpose. Since schema coverage is low, the description doesn't compensate by explaining the parameter's meaning, format, or constraints, resulting in a baseline score.
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: 'Analyze an image with AI — detect objects, colors, text, composition, quality, and mood.' It specifies the verb ('analyze'), resource ('image'), and scope of analysis. However, it doesn't explicitly differentiate from sibling tools like 'get_image_info' or 'check_job_status', which might also involve image analysis or information retrieval.
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 by listing analysis capabilities (e.g., detect objects, colors), suggesting it's for AI-based image analysis. It provides rate limit information ('3 uses/day without an account'), which helps guide usage frequency. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_image_info' or other image-processing siblings, 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context about cost ('1 credit per image') and authentication needs ('Requires PIXELPANDA_API_TOKEN'), but lacks details on rate limits, error handling, or what the generated output looks like (though an output schema exists). It adequately covers some behavioral aspects but misses others like performance or constraints.
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 appropriately sized with three concise sentences that are front-loaded with the core purpose. Each sentence adds value: the first defines the tool, the second states cost, and the third provides prerequisites and references. There is minimal waste, though it could be slightly more structured with bullet points or clearer separation of ideas.
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 (AI generation with 4 parameters) and no annotations, the description covers key aspects like purpose, cost, and prerequisites. With an output schema present, it does not need to explain return values. However, it lacks details on parameter semantics and some behavioral traits, making it slightly incomplete but mostly adequate for context.
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 description coverage is 0%, so the description must compensate for undocumented parameters. It only mentions 'UUIDs' for avatar and product, implying 'avatar_uuid' and 'product_uuid', but does not explain 'num_outputs' or 'prompt'. This leaves half the parameters (2 out of 4) without semantic clarification, failing to fully address the coverage 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?
The description clearly states the specific action ('Generate AI product photos') with precise resources ('with an avatar holding/using your product'), distinguishing it from sibling tools like 'generate_scenes' or 'generate_tryon' which have different purposes. It specifies the AI-generated nature and the avatar-product interaction, 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for usage by mentioning prerequisites ('Requires PIXELPANDA_API_TOKEN') and referencing other tools to obtain required UUIDs ('Use list_avatars and list_products to get UUIDs'). However, it does not explicitly state when not to use this tool or name alternatives, such as distinguishing it from 'generate_scenes' or 'generate_tryon' in the sibling list.
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?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the tool is 'free,' 'runs locally,' and requires 'no account,' which are valuable for understanding accessibility and cost. However, it lacks details on performance, error handling, or output behavior beyond the basic operation.
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 and front-loaded, with the core purpose stated first and additional context (free, local, no account) efficiently added. Every sentence earns its place by providing essential information without waste.
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 tool's low complexity (simple image transformation), no annotations, and an output schema that likely covers return values, the description is moderately complete. It covers the purpose and basic usage context but lacks parameter details and deeper behavioral insights, making it adequate but with gaps.
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?
The schema description coverage is 0%, so the description must compensate. It adds no information about the parameters (file_path, output_path), such as what file formats are supported, path requirements, or default behaviors for output_path. This leaves the parameters largely undocumented 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's purpose with a specific verb ('invert') and resource ('colors of an image'), and distinguishes it from siblings by specifying the transformation type ('negative'). It avoids tautology by explaining what 'invert' means in this context.
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 provides clear context for when to use this tool ('invert the colors of an image') and mentions it's 'free' and 'runs locally, no account needed,' which helps differentiate it from potential cloud-based alternatives. However, it doesn't explicitly state when not to use it or name specific sibling alternatives for similar tasks.
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 provided, the description carries full burden. It discloses key behavioral traits: 'Maintains aspect ratio by default' (default behavior), 'Free tool — runs locally, no account needed' (cost, execution environment, authentication). However, it doesn't mention file format support, error conditions, or performance characteristics.
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 perfectly concise with two sentences that each add value. The first sentence covers core functionality and key parameter behavior. The second sentence provides important execution context. No wasted words or 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?
Given 5 parameters with 0% schema coverage and no annotations, the description does reasonably well by explaining the resizing logic and aspect ratio behavior. The 'Free tool' context is helpful. With an output schema present, it doesn't need to explain return values. However, it could better address file format limitations or error scenarios.
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 description must compensate. It explains that you can 'Specify width, height, or both' and mentions 'Maintains aspect ratio by default', which clarifies the 'maintain_aspect_ratio' parameter. However, it doesn't explain 'file_path' or 'output_path' semantics, leaving 3 of 5 parameters without additional context.
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 as 'Resize an image' with specific parameters (width, height, or both) and mentions aspect ratio maintenance. It distinguishes from siblings like 'crop_image' or 'upscale_image' by focusing on resizing, but doesn't explicitly contrast with all similar tools.
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 resizing images with width/height parameters and aspect ratio control, but doesn't explicitly state when to use this vs. alternatives like 'adjust_image' or 'upscale_image'. The 'Free tool — runs locally, no account needed' provides some context but not comparative guidance.
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?
With no annotations provided, the description carries the full burden. It discloses useful behavioral traits like being free, local, and not requiring an account, but lacks details on file format support, error handling, performance limits, or whether the operation modifies the original file. It doesn't contradict any annotations.
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 front-loaded with the core purpose in the first sentence, followed by essential behavioral context in the second. Both sentences earn their place with no wasted words, making it highly efficient and easy to scan.
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 3 parameters, 0% schema coverage, no annotations, but an output schema exists, the description is moderately complete. It covers the basic purpose and key behavioral traits but lacks details on parameters, error cases, or output specifics that the output schema might handle. For a local image tool, more guidance on file handling would be beneficial.
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 description must compensate. It mentions the 'radius' parameter, adding meaning beyond the schema, but doesn't explain 'file_path' (e.g., supported formats) or 'output_path' (e.g., default behavior when null). With 3 parameters and low coverage, this provides partial but incomplete compensation.
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 specific action ('Round the corners') and resource ('of an image') with a key parameter ('with a specified radius'), distinguishing it from sibling tools like blur_image or crop_image that perform different image modifications.
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 provides clear context by stating it's a 'Free tool — runs locally, no account needed,' which helps determine when to use it versus cloud-based alternatives. However, it doesn't explicitly mention when not to use it or name specific sibling alternatives for corner-related tasks.
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 provided, the description carries the full burden and adds valuable behavioral context: it discloses rate limits ('3 uses/day'), authentication needs ('without an account' vs. 'with a PixelPanda API token'), and the free tier constraint. It does not contradict annotations, and while it could mention output behavior or error handling, it covers key operational traits.
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 appropriately sized and front-loaded, with two concise sentences: the first states the purpose and method, and the second covers usage limits. Every sentence earns its place by providing essential information without waste.
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 tool's moderate complexity (AI-based image editing), no annotations, 0% schema coverage, but an output schema exists, the description is partially complete. It covers purpose and behavioral traits but lacks parameter semantics and details on output. The output schema reduces the need to explain return values, but gaps in parameter understanding remain.
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?
The schema description coverage is 0%, so the description must compensate for undocumented parameters. It adds no meaning beyond the input schema—failing to explain what 'file_path' or 'output_path' represent, their formats, or usage. With 2 parameters and no semantic details, it does not meet the baseline for low coverage.
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 with specific verbs ('Remove text and watermarks') and resources ('from an image'), using technical details ('using AI (OCR + inpainting)') that distinguish it from sibling tools like 'remove_background' or 'add_watermark'. It goes beyond a tautology by explaining the method.
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 provides clear context for usage with rate limits ('3 uses/day without an account') and prerequisites ('Unlimited with a PixelPanda API token'), but does not explicitly state when to use this tool versus alternatives like 'remove_background' or other image editing siblings. It implies usage for text/watermark removal without 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the AI method (Real-ESRGAN), the specific scale options (2x or 4x), and important operational constraints (rate limits: 3 uses/day free, unlimited with token). It doesn't mention error conditions, processing time, or output format details, but provides substantial behavioral context beyond basic functionality.
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 perfectly front-loaded with the core functionality in the first sentence, followed by important operational details in the second. Both sentences earn their place by providing essential information about what the tool does and how it can be used. No wasted words or redundant information.
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 (AI processing with rate limits), no annotations, and the presence of an output schema (which handles return values), the description provides good contextual coverage. It explains the core functionality, method, scale options, and usage limits. The main gap is the lack of parameter documentation, but with an output schema present, the description doesn't need to explain return values.
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?
With 0% schema description coverage for all 3 parameters, the description provides no information about parameter meanings, formats, or constraints. It mentions '2x or 4x' which relates to the 'scale' parameter, but doesn't explicitly connect this to the parameter name or explain other parameters like 'file_path' and 'output_path'. The description fails to compensate for the complete lack of schema documentation.
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 specific action ('Upscale an image'), the resource ('image'), the method ('using AI (Real-ESRGAN)'), and the effect ('Enhances resolution and sharpness'). It distinguishes from siblings like 'resize_image' or 'enhance_image' by specifying the AI upscaling approach with specific scale factors (2x or 4x).
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 provides clear context about when to use this tool (for AI-based upscaling to enhance resolution/sharpness) and mentions usage limits (3/day free, unlimited with API token). However, it doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling image tools (e.g., 'resize_image' for non-AI resizing, 'enhance_image' for other enhancements).
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It helpfully adds the authentication requirement ('Requires PIXELPANDA_API_TOKEN'), which is valuable context beyond what the empty input schema provides. However, it doesn't describe other behavioral aspects like rate limits, response format, or error conditions.
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 perfectly concise with two sentences that each earn their place. The first sentence states the purpose, and the second provides essential prerequisite information. There's zero wasted text or 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?
Given that this is a simple read operation with 0 parameters and an output schema exists, the description provides adequate context. It covers the purpose and authentication requirement, though additional behavioral context about response format or error handling could enhance completeness for a tool that requires API authentication.
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 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, focusing instead on the tool's purpose and prerequisites.
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 specific action ('Check') and resources ('PixelPanda credit balance and account info'), making the purpose immediately understandable. It distinguishes itself from all sibling tools, which are focused on image manipulation operations rather than account management.
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 provides clear context for when to use this tool - specifically to check credit balance and account info. However, it doesn't explicitly state when NOT to use it or mention alternatives, though given the distinct purpose from sibling tools, alternatives may not be relevant.
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 provided, the description carries the full burden of behavioral disclosure. It effectively adds context about being a 'Free tool — runs locally, no account needed,' which informs about cost, execution environment, and authentication needs. It does not cover rate limits or detailed output behavior, but the presence of an output schema mitigates 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 appropriately sized with two sentences that are front-loaded: the first states the purpose, and the second adds crucial behavioral context. Every sentence earns its place without waste, making it efficient and well-structured.
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 (3 parameters, no annotations, but has an output schema), the description is mostly complete. It covers purpose and key behavioral traits (free, local, no account). The output schema reduces the need to explain return values, but the lack of parameter details and sibling differentiation slightly limits completeness.
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 description must compensate, but it does not mention any parameters. However, the tool has 3 parameters, and the description lacks details on their semantics (e.g., what 'file_path' expects, 'direction' options beyond 'horizontal' or 'vertical', 'output_path' usage). The baseline is lowered due to low coverage, but the description adds no param info, resulting in a minimal score.
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 specific action ('Flip an image') and the resource ('image'), with explicit direction options ('horizontally or vertically'). It distinguishes from sibling tools like 'rotate_image' or 'invert_image' by specifying the flipping operation.
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 provides clear context by stating 'Free tool — runs locally, no account needed,' which helps determine when to use it (e.g., for local, account-free operations). However, it does not explicitly mention when not to use it or name alternatives among siblings, such as 'rotate_image' for other transformations.
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 provided, the description carries the full burden of behavioral disclosure. It adds valuable context beyond the basic purpose: it specifies that this is a 'Free tool — runs locally, no account needed', which informs the agent about cost, execution environment, and authentication requirements. This addresses key behavioral traits that annotations would otherwise cover.
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 and well-structured: the first sentence states the purpose and details, and the second sentence adds crucial behavioral context. Every sentence earns its place with no wasted words, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (single parameter, no nested objects) and the presence of an output schema (which handles return values), the description is complete enough. It covers the purpose, key behavioral traits, and distinguishes the tool from siblings, leaving schema details to the structured fields.
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?
The input schema has 0% description coverage, but the description does not provide any additional information about the 'file_path' parameter beyond what the schema title implies. It does not explain what format the path should be in, supported file types, or path resolution. Given the low schema coverage, the description fails to compensate adequately, resulting in a baseline score.
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 verb 'Get' and the resource 'detailed information about an image', specifying exactly what information is retrieved (dimensions, format, file size, color mode, DPI). It effectively distinguishes this read-only analysis tool from sibling tools that perform image modifications like 'resize_image', 'crop_image', or 'convert_format'.
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 provides clear context for when to use this tool: to obtain metadata about an image file. It implicitly distinguishes it from siblings by focusing on information retrieval rather than image processing. However, it does not explicitly state when not to use it or name specific alternatives, which prevents a perfect score.
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 provided, the description carries the full burden and does well by disclosing key behavioral traits: it's a free tool with rate limits (3 uses/day without account), requires an API token for unlimited use, and returns a transparent PNG. It doesn't mention error handling or performance, but covers essential usage constraints.
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 front-loaded with the core purpose in the first sentence, followed by usage details in the second. Both sentences earn their place by providing critical information without waste, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (AI-based background removal), no annotations, and an output schema (implied by 'Returns a transparent PNG'), the description is complete enough. It covers purpose, behavioral constraints, and output, leaving parameter details to the schema and not needing to explain return values further.
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?
The schema description coverage is 0%, so the description must compensate, but it adds no information about parameters beyond what the schema provides (file_path and output_path). The baseline is 3 because the schema covers the parameters adequately, though the description doesn't enhance understanding of their semantics.
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 specific action ('Remove the background from an image using AI') and the resource ('image'), distinguishing it from siblings like 'make_transparent' (which might be more general) or 'crop_image' (which crops rather than removing backgrounds). The mention of AI further clarifies the method.
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 provides clear context for usage by stating it's a 'Free tool — 3 uses/day without an account. Unlimited with a PixelPanda API token,' which helps determine when to use based on rate limits and authentication needs. However, it doesn't explicitly compare to alternatives like 'make_transparent' or state 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it returns multiple variants (Clean Upscale, Face Enhance, AI Restore, Full Restore), has a cost (1 credit), and requires authentication (PIXELPANDA_API_TOKEN). It does not mention rate limits, error handling, or processing time, but covers essential operational aspects.
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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by key details (return variants, cost, parameters, auth). Every sentence adds value with no redundancy or fluff, making it efficient and 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?
Given no annotations, 0% schema coverage, but an output schema exists, the description is fairly complete. It covers purpose, usage context, parameters, cost, and auth. However, it lacks details on error cases, input constraints (e.g., image size/format), and output structure, though the output schema may handle the latter.
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 explains the two parameters: 'image_url (public URL)' and 'file_path (local file)', clarifying their purpose and that either can be provided. This adds meaningful semantics beyond the bare schema, though it doesn't detail format constraints or examples.
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 verb 'enhance, sharpen, and restore' with the resource 'image' and specifies the use of 'multiple AI methods'. It distinguishes from siblings like 'upscale_image' or 'adjust_image' by mentioning specific enhancement methods (Clean Upscale, Face Enhance, AI Restore, Full Restore).
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 provides clear context for when to use this tool (to enhance images with AI methods) and mentions cost (1 credit) and authentication (requires PIXELPANDA_API_TOKEN). However, it does not explicitly state when NOT to use it or name specific alternatives among the many sibling tools (e.g., vs. 'upscale_image' or 'adjust_image').
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 provided, the description carries the full burden. It discloses key behavioral traits: it returns progress and result URLs when complete, and requires PIXELPANDA_API_TOKEN for authentication. This covers output behavior and auth needs, though it omits details like rate limits or error handling.
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 front-loaded with the core purpose in the first sentence, followed by essential details in a concise manner. Every sentence adds value: the first explains the tool's function, the second covers output behavior, and the third specifies auth requirements, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter) and the presence of an output schema (which handles return values), the description is complete enough. It covers purpose, output behavior, and auth requirements, addressing key aspects without needing to detail parameters or return values explicitly.
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 1 parameter with 0% description coverage, so the description must compensate. It does not explicitly mention the 'job_id' parameter, but implies its necessity by referring to 'an AI generation job'. This adds some semantic context, though it could be more direct. Since there are 0 parameters with schema descriptions, the baseline is 4, and the description meets this by providing relevant context.
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 verb ('Check') and resource ('status of an AI generation job'), specifying what the tool does. It distinguishes itself from siblings like 'list_jobs' (which lists jobs) and other image processing tools by focusing on status checking for a specific job.
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 implies usage when needing to monitor job progress or retrieve results, but does not explicitly state when to use this tool versus alternatives like 'list_jobs' or other job-related tools. It provides clear context for checking status, but lacks explicit exclusions or named alternatives.
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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