get_docker_image_url

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. The description only states what the tool does (gets a URL) without explaining behavioral traits such as whether this is a read-only operation, if it requires authentication, what happens if the image doesn't exist (e.g., returns an error), or rate limits. For a tool with zero annotation coverage, this is a significant gap 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.

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

The description is extremely concise with a single sentence ('获取 Docker 镜像的完整 URL'), which is front-loaded and wastes no words. Every part of the sentence contributes to understanding the tool's purpose, making it efficient and well-structured for its brevity.

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 (1 nested parameter with 5 sub-parameters), no annotations, and an output schema (which likely describes the returned URL), the description is minimally complete. It states the core function but lacks details on behavior, parameters, and usage context. The output schema might cover return values, but the description doesn't address prerequisites or error conditions, leaving gaps for an AI agent.

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 provides. Schema description coverage is 0%, meaning parameter descriptions in the schema are minimal or generic (e.g., '仓库名称' - repo name). The tool has 1 parameter (a nested object with 5 sub-parameters), but the description doesn't explain what 'config' should contain, how parameters like 'registry' or 'namespace_name' affect the URL, or provide examples. It fails to compensate for the low 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 '获取 Docker 镜像的完整 URL' (Get Docker image's complete URL) states a clear purpose with a specific verb ('获取' - get) and resource ('Docker 镜像的完整 URL' - Docker image's complete URL). However, it doesn't distinguish this tool from its sibling 'build_docker_image' - both relate to Docker images but serve different functions (URL retrieval vs. image building). The purpose is clear but lacks sibling differentiation.

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's no mention of prerequisites (e.g., whether the image must already exist), context for usage (e.g., after building an image), or comparison with sibling tools like 'build_docker_image' (which might create the image first). Usage is implied only by the tool name and description, with no explicit when/when-not instructions.

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