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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds transparency by detailing the types of findings (e.g., '$3,200/month on error retries') and the analytical scope. This goes beyond what annotations alone convey, with no contradictions.

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 front-loaded with the main action and includes useful details and examples. It consists of four sentences, each contributing value, though the final 'buying trigger' sentence is somewhat promotional but still adds usage context.

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 presence of an output schema, rich annotations, and a clear description, the tool is well-specified. The description explains the tool's purpose, analysis scope, and output format, while parameter details are left to the schema. It is complete for a read-only diagnostic tool.

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 already provides 100% coverage with descriptions for both parameters (days and workspace). The description does not mention parameters, so it adds no extra meaning beyond the schema, which is the baseline for full 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 opens with a specific verb+resource: 'Detect waste and inefficiency in AI operations.' It further specifies what it analyzes (agent performance, A2A communication overhead, error costs, unused capacity, cost outliers) and gives concrete output examples, distinguishing it from siblings like a2a_audit or agent_roi.

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 clear usage context: 'This is the diagnostic tool that creates the buying trigger.' This implies when to use it (to identify waste and drive sales) but does not explicitly state when not to use it or mention alternatives, so it falls short of a 5.

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