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

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions 'structural control' but doesn't explain what this entails operationally—such as how control affects generation, whether it modifies existing images or creates new ones, potential side effects, or performance characteristics. This leaves significant gaps for a tool with 6 parameters.

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, efficient sentence with zero wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 (6 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'structural control' means, how it interacts with parameters, or what the tool returns. For a generation tool with multiple controls, more context is needed to guide effective use.

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%, so the schema fully documents all 6 parameters. The description adds no additional meaning about parameters beyond implying 'structural control' relates to the 'type' parameter. Baseline 3 is appropriate as the schema does the heavy lifting.

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 'Generate an image using structural control' states a clear purpose (generating images with control mechanisms) but is vague about what 'structural control' means and doesn't distinguish from sibling tools like 'generate', 'img2img', or 'inpaint'. It doesn't specify what makes this tool unique compared to those alternatives.

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 the sibling tools ('generate', 'img2img', 'inpaint'). There's no mention of appropriate contexts, prerequisites, or exclusions. The agent must infer usage from the tool name and parameters 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?

With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It mentions generation but doesn't cover critical aspects like whether this is a read-only or destructive operation, potential rate limits, authentication needs, or what the output entails (e.g., image format, storage location). This leaves significant gaps in understanding the tool's 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 extremely concise and front-loaded with a single, clear sentence that directly states the tool's core function. There is no wasted language or redundancy, making it efficient and easy to parse, though this brevity contributes to gaps in other dimensions like guidelines and transparency.

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 a 6-parameter image generation tool with no annotations and no output schema, the description is incomplete. It fails to address behavioral traits, usage context, or output details (e.g., what is returned, error handling), leaving the agent under-informed for effective tool invocation in a real-world scenario.

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 no parameter semantics beyond what the input schema already provides, as schema description coverage is 100%. The schema thoroughly documents all 6 parameters, including enums for 'model' and 'aspect_ratio', defaults, and dependencies (e.g., 'width'/'height' ignored if 'aspect-ratio' set). Thus, the description meets the baseline but doesn't enhance parameter understanding.

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 with a specific verb ('generate') and resource ('image from a text prompt'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'img2img' or 'inpaint' which likely also generate images but from different inputs, leaving room for potential confusion about when to choose this specific tool.

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 like 'control', 'img2img', or 'inpaint'. It lacks context about prerequisites, such as needing a text prompt as input, or exclusions, like not being suitable for image-to-image transformations. This absence leaves the agent without clear direction 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?

No annotations are provided, so the description carries the full burden. It states the tool generates an image but doesn't disclose behavioral traits such as whether it overwrites files, requires specific permissions, has rate limits, or what the output format/behavior is (e.g., file creation, error handling). This is a significant gap for a tool with 8 parameters and no 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 a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for the tool's complexity, 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.

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

Given the tool's complexity (8 parameters, no annotations, no output schema), the description is insufficient. It doesn't explain the tool's behavior, output (e.g., file saved to disk), or usage context relative to siblings. For an image generation tool with multiple parameters, more detail is needed to guide effective use.

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 description coverage is 100%, so the schema already documents all parameters well (e.g., 'image' as input path, 'prompt' for text, 'strength' for generation intensity). The description adds no additional meaning beyond implying the 'image' parameter is used as a reference, which is somewhat redundant with the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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: 'Generate an image using another image as reference.' It specifies both the action ('generate') and the resource ('image'), though it doesn't explicitly differentiate from sibling tools like 'generate' or 'inpaint' beyond the reference image aspect.

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 like 'generate' (which likely generates from text only) or 'inpaint' (which might modify parts of an image). It mentions using an image as reference but doesn't clarify scenarios 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 carries the full burden of behavioral disclosure. It states the action ('inpaint') but doesn't explain what inpainting entails (e.g., filling masked areas based on a prompt), potential side effects, permissions needed, or output behavior. This leaves significant gaps for a tool that modifies images.

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, efficient sentence with zero waste—'Inpaint an image using a mask'—making it highly concise and front-loaded. Every word earns its place by conveying the core action and resource.

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 an image inpainting tool with no annotations and no output schema, the description is insufficient. It doesn't explain what inpainting does, how the output is handled, or any behavioral traits, leaving the agent with incomplete context for proper tool selection and 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?

Schema description coverage is 100%, so the schema already documents all parameters (image, prompt, mask_shape, position, output) with descriptions and enums. The description adds no additional meaning beyond what the schema provides, such as explaining how the prompt influences inpainting or how mask shape/position interact. Baseline 3 is appropriate when the schema does the heavy lifting.

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 'Inpaint an image using a mask' clearly states the action (inpaint) and resource (image with mask), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'img2img' or 'generate', which might also involve image manipulation, so it's not a perfect 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 provides no guidance on when to use this tool versus alternatives like 'img2img' or 'generate'. It lacks context about specific use cases, prerequisites, or exclusions, leaving the agent to infer usage based on the name alone.

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