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. However, it offers no information on whether this tool is read-only or mutating, what permissions or rate limits apply, what output format to expect, or any side effects. The phrase 'with statistics' hints at computation but lacks specifics, failing to compensate for the absence of structured 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 concise—a single phrase—but this brevity results in under-specification rather than efficiency. While it is front-loaded, it lacks the necessary detail to be helpful, making it more of a placeholder than a well-structured explanation. It earns a middle score for being short but loses points for failing to convey meaningful information.

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 (implied by aggregation and statistics), the absence of annotations, 0% schema description coverage, and no output schema, the description is severely incomplete. It does not address key aspects like data sources, aggregation methods, output format, or error handling, leaving the agent with insufficient 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?

The input schema has one parameter ('period') with 0% description coverage, meaning the schema provides no semantic details. The description does not mention this parameter at all, offering no compensation for the lack of schema documentation. This leaves the agent with no understanding of what 'period' represents or how to use it effectively.

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 'Aggregate metrics with statistics' is vague and tautological—it essentially restates the tool name 'metrics_aggregate' without specifying what metrics are aggregated, from what source, or what statistics are computed. It fails to distinguish this tool from siblings like 'metrics_collect', 'metrics_query', or 'metrics_dashboard', leaving the purpose unclear beyond a generic aggregation concept.

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. It does not mention any prerequisites, context, or comparisons to sibling tools (e.g., 'metrics_collect' for data collection or 'metrics_query' for querying), making it impossible for an agent to determine appropriate usage scenarios without external knowledge.

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