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

As no annotations are provided, the description carries the full burden of behavioral disclosure. It clearly explains return modes (file path or base64), the important relative-path resolution behavior tied to the server's cwd, and default size behavior. This is meaningful context beyond basic write intent, though error handling and permissions are not covered.

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 clear Args, Returns, and Example sections. The relative-path warning is essential and the example adds practical value. Every sentence contributes, with no fluff 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?

For a moderately simple tool, the description covers parameter details, return type, and a concrete example. The absence of error handling and explicit tool-selection guidance is a minor gap, but the information provided is sufficient for typical usage, especially given the output schema exists.

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?

Despite the input schema having 0% description coverage, the description thoroughly documents all three parameters: image_id format with an example, size options with valid values, and output_path with a critical warning about absolute versus relative paths. This fully compensates for the schema's absence of descriptions.

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 'Download an image to local storage or return base64 encoded data,' using a specific verb and resource. This distinguishes the tool from sibling tools like search_stock_images and get_image_details.

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 usage details for parameters but does not explicitly state when to use this tool versus alternatives. The intended use is implied by the tool name and purpose, but no explicit when-to-use or when-not-to-use guidance is given.

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 explicitly states the return behavior ('Detailed image information or None if not found') and documents the default behavior of include_attribution via an environment variable. This adds useful context beyond the input schema. However, it does not mention any side effects, permissions, or rate limits, though for a read-only 'get' operation this is likely acceptable.

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, using an Args/Returns format. It is front-loaded with the primary purpose, includes a concrete example for the main parameter, and has no wasted words. Every sentence earns its place.

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 (two parameters, one required), the presence of an output schema, and the lack of annotations, the description is sufficiently complete. It covers the core purpose, both parameters, the default behavior of the optional parameter, and the special return case (None if not found). This gives the agent enough context to use the tool correctly.

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 must compensate, and it does thoroughly. Each parameter is explained with meaning: image_id gets an example ('pexels_12345') and clarification that it is provider-prefixed, while include_attribution is explained with its purpose and default behavior. This adds significant value over the bare schema definitions.

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: 'Get detailed information about a specific image.' This uses a specific verb ('Get') and resource ('detailed information' for 'a specific image'), which naturally distinguishes it from sibling tools like search_stock_images and download_image. The 'specific image' phrasing indicates this is for retrieving details on an already-identified image, not for discovery or file retrieval.

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 when to use the tool by requiring an image_id and describing it as a lookup operation, but it does not explicitly contrast with alternatives. While it's clear from the name and parameters that you need an existing image ID, there is no explicit 'use this instead of search_stock_images when you have an ID' guidance. The context is clear enough, but exclusions/alternatives are not explicitly stated.

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 adds value by specifying that invalid or unavailable providers return an error instead of silently substituting, and that include_attribution defaults to an environment variable. However, it omits potential auth requirements, rate limits, or side effects, keeping it slightly below a perfect score.

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-organized with a clear first sentence stating the purpose, followed by structured Args and Returns sections. Every line adds essential detail without unnecessary verbosity. It is appropriately sized and front-loaded, making it easy for an agent 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?

Given the tool's moderate complexity (6 parameters, multi-provider integration), the description covers all parameters and notes error handling and defaults, which is substantial. The presence of an output schema means return values need not be explained in detail. It misses a few nuances, such as the behavior when providers is omitted (default null likely means all providers) and potential authentication prerequisites, so it isn't fully 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 provides only types and titles with zero description coverage, so the description must compensate. It fully explains each parameter: query string, providers with valid values and case-insensitivity, per_page, page, sort_by with allowed values, and include_attribution with its env-var default. This is comprehensive parameter documentation that far exceeds the schema's minimal information.

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: 'Search for royalty-free stock images across multiple providers.' This is a specific verb (search) plus a resource (stock images) and scope (multiple providers). It effectively distinguishes from sibling tools get_image_details and download_image, which handle post-search operations.

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 communicates the basic intent of searching images but provides no explicit guidance on when to prefer this tool over alternatives. It neither names sibling tools nor instructs the agent to use get_image_details for specific image metadata or download_image for fetching. Usage is implied by the function name rather than explicitly stated, earning a mid-range score.

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