Miyabi MCP Bundle

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 that the tool lists images 'with size and tags' and helps find 'dangling images to clean up,' which gives some context about output format and a practical application. However, it doesn't describe critical behavioral aspects like whether this is a read-only operation, potential performance impacts, or how results are formatted (e.g., as a table or JSON). For a tool with zero annotation coverage, this leaves significant gaps.

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 well-structured: two sentences that efficiently convey the tool's purpose and a key use case. Every word earns its place, with no redundancy or unnecessary elaboration, making it easy to parse 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 moderate complexity (listing images with filtering options), no annotations, and no output schema, the description is somewhat complete but has notable gaps. It covers the basic purpose and a use case but lacks details on output format, error conditions, or behavioral constraints. It's adequate for a simple listing tool but could benefit from more context to fully guide an 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 input schema has 100% description coverage, with clear documentation for both parameters ('all' and 'dangling'). The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining how 'dangling' relates to cleanup or default behaviors. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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: 'List Docker images with size and tags.' It specifies the verb ('List') and resource ('Docker images') with additional details about what information is included. However, it doesn't explicitly differentiate from sibling Docker tools like 'docker_ps' or 'docker_inspect' beyond the dangling images cleanup mention.

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 some implied usage guidance with 'Find dangling images to clean up,' suggesting a specific use case for the tool. However, it doesn't explicitly state when to use this tool versus alternatives like 'docker_ps' (which shows containers, not images) or provide clear exclusions. The guidance is helpful but not comprehensive.

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