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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. However, the description adds no behavioral detail beyond a purpose statement: it does not reveal what the output looks like, what data scope is examined, whether it returns examples, or any operational constraints.

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 a single concise sentence with no filler or redundancy. It front-loads the core action and then gives the purpose, making it efficiently scannable for an agent.

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?

With ten parameters, five required ones, no output schema, low parameter documentation, and many similar sibling tools, the minimal description is not enough for reliable invocation. It fails to explain return values, required parameter semantics, or how this tool fits among the other analysis tools.

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 only 40%, leaving most parameters undocumented. The tool description contains no parameter-level guidance at all, so it fails to compensate for the low schema coverage. An agent must infer the meaning of required fields like symbol, timeframe, startDate, endDate, and source.

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 uses a specific verb ('Find') and a specific analytical resource ('recurring loss patterns'), with a clear downstream purpose ('drive the next falsifiable hypothesis'). This distinguishes it from sibling analysis tools that target other aspects such as risk management, trade features, or overfitting.

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 phrase 'to drive the next falsifiable hypothesis' implies a workflow context, but the description does not explicitly state when to prefer this tool over the many sibling analyze_* tools. There are no exclusions, alternatives, or conditions, so usage guidance remains implied rather than explicit.

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