YouCam for Fashion & Retail

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

The description adds the gender requirement and the 'ask if missing' behavior, which is useful. However, it also claims 'visualize products instantly through camera', which could mislead since the tool actually accepts image URLs or file IDs, not a live camera feed. It also does not disclose the async/polling behavior or what the output image represents, so transparency is limited.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description opens with unnecessary marketing fluff ('AR makes luxury bag shopping a tangible experience!...') and contains a typo ('through camera.gender must be...'). The key usage instruction is buried at the end, so the description is not front-loaded and contains wasted words.

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

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

The tool has a complex request schema with multiple oneOf combinations of URL/file IDs, plus a polling parameter. The description does not explain these variants, the meaning of src_file_url vs ref_file_url, or the polling behavior. It only addresses gender handling. Given the complexity, the description is incomplete for an agent to use the tool effectively.

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

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

The schema already documents each parameter, but the description adds a critical rule not present in the schema: 'gender must be explicitly provided by the user. If missing, ask the user for clarification and set the parameter once received.' This provides actionable meaning beyond the schema's simple 'Gender of the person in the image.'

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description mentions 'handbags' and 'visualize products', which suggests a virtual try-on for bags, but it is phrased as marketing ('AR makes luxury bag shopping a tangible experience') rather than a clear functional statement. It does not explicitly state that the tool takes a user photo and a bag image to produce a composite, leaving the exact operation vague.

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

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

The only usage guidance is the instruction that 'gender must be explicitly provided by the user. If missing, ask the user for clarification and set the parameter once received.' This is a parameter-level workflow hint but there is no guidance on when to use this tool versus sibling try-on tools, nor any exclusions or prerequisites for tool selection.

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

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

The description is entirely marketing ('great shopping satisfaction', 'compelling shopping flow') and discloses no behavioral traits such as whether the operation is asynchronous, what it modifies, or how results are returned. Annotations indicate it is not read-only, but the description adds no context beyond that, leaving the agent without operational expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a verbose, unstructured marketing paragraph full of superlatives ('hyper-realistic', 'effortless yet high-quality'). It is not front-loaded with the core function; instead, it leads with sales language. Every sentence could be removed without any loss of operational information, making it the opposite of concise.

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

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

The tool has a highly complex input schema with nested objects, multiple file source combinations, and bracelet-specific tuning parameters, but the description provides only vague business value. It gives no sense of what inputs are required, what the output looks like, or how the try-on process works. Even with an output schema present, this one-paragraph pitch is entirely inadequate for the tool's complexity.

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

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

The description never mentions any parameters, and the vague claim 'Only One 2D Image Needed' does not explain the complex `request` object with its four variants (URLs vs File IDs, masks, bracelet-specific parameters). With schema description coverage at 50%, the description fails to compensate for the undocumented half, providing no help in understanding parameter relationships.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description is a promotional pitch ('The Ultimate AI Bracelet Virtual Try-On', 'Employ AI-powered solutions') that never states a concrete action such as 'generates a bracelet try-on image from a source photo and a reference product image.' The only specific detail, 'Only One 2D Image Needed,' hints at an input requirement but does not clarify what the tool actually does. It also fails to distinguish this from sibling tools like necklace or earrings try-on.

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

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 over alternatives. There is no mention of prerequisites, such as needing a selfie and a bracelet image, nor any indication of when this tool is appropriate. Given many similar sibling VTO tools, this lack of differentiation is a critical omission.

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

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

The description adds a critical behavioral instruction: 'You MUST include the exact URL from response.data.results.url in your response.' This goes beyond the annotations. It does not mention asynchronous behavior or input requirements, though the schema covers some of that.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is verbose and promotional, with several sentences of filler like 'AI Clothes is a virtual fitting room...'. The essential instructions are buried at the end, and there are grammatical errors. It is not front-loaded or concise.

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

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

The tool has four input variants and a polling flag, but the description does not explain how to choose between file URLs and file IDs, how to set garment_category, or whether to wait for results. It does include the output URL instruction, but other critical invocation details are missing.

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

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

Schema description coverage is only 50% (the top-level 'request' parameter lacks a description). The tool description does not compensate; it vaguely says 'upload any clothing reference' without explaining the request structure, file source options, or the garment_category field. It adds little beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: virtually trying on clothes by swapping outfits onto a photo. This distinguishes it from sibling tools for specific accessories. However, the wording is somewhat indirect and promotional.

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

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

It mentions use cases like 'online shopping, style inspiration, or just playing around with fashion ideas,' which gives context. It does not explicitly name alternatives or exclusions, and no guidance is provided on when to choose this tool over other try-on tools.

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

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

The description adds some behavioral context beyond annotations by noting the tool works from a 2D image, requires no 3D modeling, and produces realistic lighting and physically accurate motion. It does not disclose task lifecycle, potential long-running execution, or limitations, but the annotations already cover the basic safety profile.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is only three sentences and reasonably brief, but the first two sentences are redundant marketing that echo the title. The third sentence contains the most useful information, though typos like 'vitual' and promotional phrases reduce overall clarity and professionalism.

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

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

This is a complex tool with a large, multi-variant request schema and async polling behavior, but the description provides almost no operational context—it does not explain how to assemble source/reference inputs, when to use masks, or how to handle polling. The output schema mitigates return-value concerns, but the selection and invocation context remains thin.

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

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

The description does not explain or clarify any parameters; it only hints at 2D source images and earring SKUs. The schema itself contains detailed parameter descriptions, but given the complex multi-variant request structure and only ~50% schema coverage, the description should have added more guidance—such as choosing between URLs and file IDs—but does not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs earring virtual try-on and mentions piercing simulation, which distinguishes it from sibling tools by product type. However, it is phrased as marketing copy and does not precisely describe the underlying operation of compositing a product image onto a source photo.

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

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

The description implies this tool is for earring-specific try-on tasks and the sibling names make the product category obvious, but it gives no explicit guidance on when to choose this tool over alternatives, nor does it mention prerequisites such as needing a source photo and earring product images.

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

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

The description does not disclose that this is a non-idempotent task-based operation (polling parameter), requires publicly accessible URLs, or any side effects. It only provides promotional content, adding no transparency beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a verbose marketing paragraph with exclamation marks and imperatives like 'Transform your look!' It fails to front-load the functional purpose and wastes space on 'fresh fabric updates' and 'see and feel fabrics.' Not concise or structurally helpful.

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

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

Despite having a moderately complex input schema with multiple request variants and polling, the description provides no operational context such as how to obtain templates, file requirements, or async behavior. It is entirely inadequate for correct tool invocation.

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

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

The description mentions 'photo mode' and 'fabric styles' but never references parameters like template_id, src_file_url, src_file_id, or polling. The input schema already provides descriptions, but the description adds no additional parameter semantics to assist the agent.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses marketing language like 'Transform your look with stunning realism' and 'Explore unique fabric styles with photo mode' but never explicitly states the tool performs a virtual try-on of fabric on a provided photo using a template. It is vague and doesn't clearly identify the core operation or distinguish it from sibling tools.

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

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

No guidance on when to use this tool versus sibling tools (e.g., AI-Clothes-Virtual-Try-On) or prerequisites like listing templates or uploading files. There is no mention of when to choose this tool over alternatives.

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

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

The annotations (readOnlyHint, idempotentHint, destructiveHint) already establish that this is a safe, non-destructive read operation. The description adds no additional behavioral context, such as what the templates represent or how they are used, but it is consistent with the annotations and does not contradict them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence with no filler or redundant information. It is front-loaded with the core verb and object, making it immediately parseable by an AI agent.

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

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

The description is adequate for a simple list operation, and the presence of an output schema covers return values. However, it lacks context about how this tool relates to sibling virtual try-on tools, specifically that the templates are likely inputs for those operations. A more explicit connection would enhance completeness.

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

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

The tool has zero parameters, and the schema confirms this with 100% coverage. The description does not need to explain any parameters since none exist, and the baseline score for zero-parameter tools is 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'List' and resource 'predefined templates,' clearly indicating a read-only enumeration operation. It distinguishes from sibling try-on tools which perform actions rather than list templates, though the description itself does not explicitly mention 'fabric' or the domain context beyond the tool name.

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

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

No guidance is provided on when to use this tool versus alternatives, such as other try-on tools or discovery methods. There is no mention of typical workflows, prerequisites, or exclusions, leaving the agent to infer usage solely from the tool name and the fact that it lists templates.

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

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

Annotations already indicate non-read-only behavior, and the description adds no details about side effects, costs, or long-running tasks. The appended instruction that gender must be explicitly provided and that the agent should ask for clarification is a useful behavioral/enforcement note, but the rest is promotional and adds nothing about how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is verbose and filled with marketing claims ('Elevate engagement, boost confidence') that earn no functional value. The critical gender instruction is awkwardly appended to a long promotional paragraph, making it difficult to parse and not front-loaded with the key technical purpose.

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

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

For a tool with multiple request schema variants, an output schema, and polling options, the description is incomplete. It does not clarify how to choose between URL and ID inputs, what the reference vs source images mean, or what the workflow should be, leaving the agent to infer everything from the schema.

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

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

Schema description coverage is 50%, so the description needs to compensate, but it does not. The only parameter-related content is the gender requirement, which merely echoes the schema's 'required' flag. There is no explanation of src_file_url vs ref_file_url, file IDs, style options, or polling behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as a virtual try-on for headwear, mentioning hats and headbands, which distinguishes it from sibling tools for other accessories. However, the meaning is buried in marketing language ('unmatched precision and realism') rather than a crisp functional definition like 'Generate a try-on image from a source and reference image.'

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

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 the many sibling virtual try-on tools, nor any context about customer scenarios. The only prescriptive sentence is about requiring the gender parameter, which is a parameter-level detail rather than usage guidance.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no additional behavioral context, such as how categories affect results or any rate limits, but it does not contradict the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence with no filler or redundant content. Every word contributes to the purpose, and it is front-loaded with the action verb.

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

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

The tool is simple with one parameter, complete schema, and annotations. The output schema exists, so return values need not be explained. However, the description lacks any broader workflow context, such as when fetching pattern names is necessary, which is a minor gap.

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

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

Schema coverage is 100%; the categories parameter is fully described with an enum of allowed values. The description adds no extra meaning about parameter semantics, hitting the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear action and resource: 'Get AI Makeup VTO available pattern names.' It explicitly identifies the tool as a getter for pattern names specific to makeup VTO, distinguishing it from sibling VTO tools.

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

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. There is no mention of prerequisites, typical use cases, or exclusions, leaving the agent to infer usage from the schema alone.

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

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

Annotations already declare readOnlyHint=false, so the agent knows this is not a pure read operation. The description adds no behavioral details such as async processing, polling requirements, result format, or limitations; it only makes quality claims like 'ultra-realistic' and 'physically accurate motions', which do not inform invocation behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description opens with marketing slogans ('Luxurious Look and Feel') and repeats hyperbolic adjectives ('ultra-realistic', 'lifelike', 'sophisticated') that add no operational value. The core functional sentence is buried at the end, making it poorly structured and unnecessarily verbose.

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

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

This is a complex tool with multiple request schema variants (URL vs File ID combinations), yet the description gives no overview of these options, prerequisites like publicly accessible URLs, or how to use upload APIs. The output schema exists, but the description still leaves the agent without a map of the tool's full input space.

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

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

Schema description coverage is only 50% (only the 'polling' parameter is described at the top level). The description does not mention or explain any parameters, offering no guidance on the complex 'request' object or its multiple URL/File ID variants, so it fails to compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Create realistic and dynamic necklace virtual try-on from a 2D image', which clearly identifies the action (create) and resource (necklace virtual try-on). It also implicitly differentiates from sibling accessory VTO tools by focusing on 'necklace', though the phrasing is promotional and does not crisply define the exact input/output relationship.

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

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

No explicit when-to-use or alternative guidance is provided. The purpose of necklace try-on is implied by the tool name and repeated 'necklace' references, and the phrase 'from a 2D image' hints at the input context, but the description never states when this tool should be chosen over sibling accessory VTO tools or how it relates to file upload tasks.

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

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

Annotations already indicate this is a non-read-only, open-world operation. The description adds that it produces AR-based results and suggests 2D images, but does not disclose asynchronous polling behavior, potential side effects on uploaded data, or time expectations. With annotations present, this is acceptable but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences and front-loads the core purpose. The second sentence is mildly promotional ('effortless yet high-quality') but does not waste much space. It is concise overall.

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

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

Given the highly complex nested request schema (four union variants, many ring parameters, mask fields), the description is far too thin. It does not explain how to construct a valid request, the polling option, or the nature of the task (e.g., synchronous vs. async). The output schema exists but does not compensate for missing request semantics.

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

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

Schema description coverage is only 50%, and the description does not compensate. It only mentions uploading images, providing no insight into the complex 'request' object, optional masks, or the polling parameter. Since half the parameters are undocumented in the schema, the description fails to fill the gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: creating AR ring or engagement ring try-ons from uploaded images. This specific verb+resource combination (create + ring try-on) distinguishes it from sibling tools for other jewelry types like necklaces or earrings.

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

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

The phrase 'Ring or Engagement Ring Try Ons' implies this tool is for rings, but there is no explicit mention of when to use it vs. alternatives or exclusions. The statement 'You Only Need to Upload Images' offers a basic input requirement but no comparative guidance.

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

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

The description adds context about AR simulation and high-fidelity visualization, but it does not disclose operational traits such as asynchronous execution, polling behavior, or the nature of the output (e.g., a generated image). Annotations already mark the tool as not read-only and not destructive, and the description does not contradict them. It also includes a behavioral requirement for gender, which is useful context beyond the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is padded with marketing language like 'Enhance your fashion experience' and 'high-fidelity AR simulation,' repeating the concept of virtual try-on multiple times. The useful instruction about gender is appended awkwardly after a space, forming 'anywhere.gender' typo. It could be trimmed to one or two sentences focusing on purpose and the gender requirement.

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

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

Given the complex input schema with four anyOf variants, a polling parameter, and an output schema, the description is far too high-level. It omits guidance on choosing between URL and ID inputs, the asynchronous nature of the task, and the expected result. The gender requirement is the only operational detail provided, which is insufficient for an agent to confidently invoke this tool.

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

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

The description explicitly stresses that gender must be provided and instructs the agent to ask if missing, adding semantic weight to that parameter beyond the schema's required flag. However, it does not clarify the meaning of src_file_url vs ref_file_url or the file ID variants, and with only 50% schema description coverage, it does not fully compensate. The mention of 'styles and colors' loosely aligns with the style parameter but adds little detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as a virtual scarf try-on service, using active language like 'drape scarves over their outfits' and 'see how patterns flow in real life.' This distinguishes it from sibling tools for other accessories/clothing. The resource (scarf) and action (virtual try-on) are both explicit, earning a 5.

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

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

The description implies usage for shoppers interested in virtually trying on scarves, but it does not explicitly contrast with sibling try-on tools or state when not to use it. It does provide a clear operational guideline that 'gender must be explicitly provided' and instructs the agent to ask for clarification if missing, which is helpful. However, this is not about tool selection, so the overall guidance is only 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.

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

The description fails to disclose key behavioral traits such as asynchronous processing (polling parameter), input requirements beyond gender (e.g., publicly accessible URLs), or that the tool generates a composite image. Annotations provide safety hints (readOnlyHint=false, etc.) but no contextual details. The gender note is the only added behavioral context, and it is parameter-focused rather than tool behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is verbose, filled with marketing language ('Step into the future', 'high-fidelity AR simulation', 'thrill of an in-store experience') that adds no operational value. The critical instruction about gender is appended awkwardly to the end after a period, creating a run-on sentence without proper separation. It is not front-loaded and fails to communicate vital information efficiently.

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

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

Despite a complex schema with multiple request variants and an output schema, the description provides no information about what the task does beyond 'see how shoes look and fit.' There is no mention of how to handle file uploads, when to use file IDs versus URLs, the meaning of polling, or the expected result format. The description is entirely inadequate for guiding correct invocation of this tool.

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

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

The description adds minimal value beyond the input schema. The only parameter mentioned is gender, asserting it must be explicitly provided and asking for clarification if missing—this is already implied by the required field and enum in the schema. With schema description coverage at 50% (polling described, request not), the description does not compensate for the missing 'request' description or explain the differences between file URLs and file IDs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as an AR/AI shoes virtual try-on, specifying the resource (shoes) and the action (see how styles look and fit). This naturally differentiates it from sibling tools for other products like bags, clothes, and hats. However, the purpose is embedded in promotional language rather than a crisp, technical statement, slightly reducing clarity.

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

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

No explicit guidance on when to use this tool versus alternatives is provided. The only usage-related instruction is the appended note about gender being explicitly required and asking for clarification if missing, which addresses parameter handling rather than tool selection. The openWorldHint annotation is not leveraged in the description.

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

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

Annotations indicate non-read-only, non-idempotent, and non-destructive behavior, but the description adds little beyond that. It does not disclose the async/polling behavior hinted by the 'polling' parameter, nor does it mention the need for masks or multiple images. The phrase 'instantly try on' could actually mislead about task latency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description contains marketing fluff ('top-notch watches', 'sets us apart', 'easier than ever') that provides no operational value. The core message could be conveyed in one sentence. It is not efficiently structured for an AI agent.

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

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

Given the complexity of the schema (four request variants, nested objects, optional masks, adjustable watch parameters), the description is far too thin. It does not explain the different input modes (URL vs File ID), the role of masks, or how the output is produced, despite an output schema existing.

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

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

The description adds essentially no parameter information. It mentions 'one 2D image' but the schema involves source images, reference images, optional masks, and watch-specific tuning parameters. With 50% schema coverage, the description does nothing to compensate for the gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as a virtual try-on for AR watches, using phrases like 'Try-On AR Watches' and 'AR-Watches App'. This differentiates it from sibling tools for other products, though the marketing tone adds some noise. It is a specific verb+resource statement.

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

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

No explicit guidance is provided for when to choose this tool over the sibling try-on tools. The only clue is the product category in the name, but the description itself does not mention alternatives, prerequisites, or exclusions.

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

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

With no annotations provided, the description compensates by disclosing key behavioral traits: it uploads directly from the browser, bypasses sandbox egress restrictions, and returns file IDs. It does not mention file size limits or other edge cases, but covers the most important behaviors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is divided into clear sections with line breaks, starting with purpose, then usage, then fallback behavior. It is somewhat long, but every sentence adds unique value, and the structure improves scannability.

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

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

Given the simple schema (one optional parameter) and the presence of an output schema, the description covers trigger conditions, alternatives, fallback role, and technical behavior. No significant gaps remain.

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

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

The schema provides a full description for the single optional parameter task_type, including an enum and default value. The tool description adds no additional parameter semantics, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb ('uploading'), the resource (images/videos with supported formats), and the output (file IDs for YouCam AI tools). It distinguishes itself from the sibling AI tools and from upload_file by presenting itself as an interactive drag-and-drop widget.

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

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

Explicitly states when to use: when the user wants to upload/select an image or video, or before any AI-* tool requiring src_file_id or ref_file_id. It also names the alternative (Get-Upload-API-Info) and specifies a mandatory fallback scenario, including network restrictions and host_not_allowed.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so safety profile is covered. The description adds one useful behavioral detail: values are consistent with the external pricing URL, which helps set expectations for accuracy. However, it doesn't describe pagination behavior, the structure of the response, or whether any authentication is required beyond what annotations imply.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core purpose, and provides a useful reference URL. Every word earns its place with no wasted text.

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

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

Given the tool's simplicity (a read-only cost lookup with a nested request object and output schema), the description is largely complete. The URL to authoritative pricing values strengthens completeness. Missing a brief note on pagination behavior is a minor gap, but the output schema likely documents return structure. Overall, shows adequate completeness for this context.

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

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

Schema description coverage is 0%, so the description carries no parameter details. The input schema defines 'request' as a nested object with page_size and starting_token, but the description doesn't mention pagination. With 1 parameter (request object) and no description coverage, the description adds no meaning beyond schema. However, the schema is mostly self-explanatory, and a baseline of 3 is appropriate since the agent can infer pagination from the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool checks unit consumption for each API and provides a reference URL for pricing values. It uses the specific verb 'Check' and resource 'unit consumption for each API', which makes the purpose clear. However, it doesn't explicitly distinguish it from sibling tools beyond their obvious domain differences (virtual try-on vs. cost lookup).

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

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

The description implies usage for checking API pricing/consumption but doesn't explicitly state when to use it vs. alternatives or provide exclusions. The URL provides authoritative reference context, but no explicit guidance on when to invoke this tool over others.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description need not repeat these. It adds useful context about checking tasks that were left processing and mentions timeout scenarios. This goes beyond the annotations with practical behavioral details about when the tool is appropriate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear one-sentence summary followed by a focused bulleted list of when-to-use scenarios. It is slightly longer than minimal but every sentence adds value; no filler or redundancy.

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

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

Given there is an output schema, the description does not need to explain return values. It effectively covers what the tool does and when to use it. It could mention the polling behavior as a context nuance, but overall it is complete for a status-checking tool with good annotations and schema.

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

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

Schema description coverage is 100%, with all four parameters described clearly in the schema. The description itself does not add further parameter-level meaning beyond what is in the schema, so the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves the current status and results of a previously initiated AI processing task. It uses a specific verb ('Retrieves') and specific resource context ('status and results of a previously initiated task'), and it is distinct from sibling tools that initiate specific AI processing tasks.

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

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

The description provides explicit use cases via a bulleted 'WHEN TO USE THIS TOOL' section, such as checking on a task from a previous session or resuming a conversation. It does not explicitly state when not to use it or mention alternatives, but the guidance is clear and context-rich, warranting a 4 rather than 5.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful behavioral context: the no-retry policy, immediate fallback to the File Upload Widget, and the instruction not to ask for a public URL. These are not redundant with annotations and help the agent handle failure scenarios, though the description could also mention that the response format is provided by the output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: three sentences that front-load the primary purpose, then provide usage guidance and fallback behavior. Every sentence adds value. The '/n' appears to be a formatting artifact and does not detract from clarity.

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

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

For a simple read-only info tool with an output schema, the description covers the essential aspects: what it returns, when to use it, and what to do on failure. It could mention that the endpoint depends on the task_type parameter or that the response contains actual API details, but given the rich enum in the schema and the output schema, the description is sufficiently complete.

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

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

The input schema fully describes the single 'task_type' parameter with a comprehensive enum list and a clear description. The tool description does not add any additional parameter-level information, but with 100% schema coverage, the baseline of 3 is appropriate. The enum itself conveys the accepted values, so no further explanation is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns the upload API endpoint and example request/response for uploading images or videos to YouCam AI. This specific verb+resource description distinguishes it from sibling task tools that perform actual AI operations rather than providing API info.

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

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

It explicitly states when to use the tool ('Use when the user wants to upload an image/video via the API'), provides a clear fallback to the File Upload Widget if upload fails, and includes a specific no-retry instruction and a prohibition on asking for a public URL. This is excellent guidance for an agent to select and invoke correctly.

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

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

With no annotations, the description carries the burden of behavioral disclosure. It honestly describes the side-effecting upload behavior, the base64 input format, and the file_id(s) return value, but it omits potential constraints like authentication, file size limits, or persistence implications. This adds some transparency but not deep context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no redundant words. It immediately names the action and key details, making it easy to scan.

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

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

Despite having an output schema, the description is incomplete for correct invocation because it does not explain the required 'task_type' parameter or connect the upload step to the sibling try-on workflows. An agent cannot infer how to populate task_type from this description alone.

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

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

The input schema has 0% description coverage, so the description must compensate. It only clarifies that files are base64-encoded media, giving partial meaning to the 'files' parameter, but it completely ignores the required 'task_type' parameter and the object structure of each file entry.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific action (upload), resource (base64-encoded media files), destination (YouCam API), and result (returns file_id(s)). It differentiates from the many try-on sibling tools, though a similarly named 'File-Upload' sibling exists and is not explicitly distinguished.

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

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

No guidance is provided about when to use this tool versus alternatives such as File-Upload or Get-Upload-API-Info. The description only states what the tool does, not under what circumstances it should be invoked.

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