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

Annotations already indicate readOnly, idempotent, and non-destructive behavior, and the description adds valuable context beyond those: results are 'deterministic empirical observations only,' do not predict future prices, and are not investment advice. It also discloses the conservative sample-size-based confidence approach, which is a behavioral trait not present in 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 front-loaded with the core purpose, then follows with the question it answers, the output contents, and important caveats. Every sentence earns its place and there is no redundant restatement of the tool name or schema fields.

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?

The description covers purpose, supported scope, output characteristics, statistical windows, path classifications, confidence handling, and non-advice limitations. An output schema exists, so return values do not need to be re-explained. Nothing critical is missing for an agent to correctly select and invoke the 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?

Schema description coverage is 100%, so the schema already explains eventType, instrument, limit, and referencePeriod clearly. The description adds some context by mentioning 'similar to a target CPI event' and 'U.S. CPI releases,' but it does not substantially expand on parameter meaning beyond what the schema provides. Baseline 3 is appropriate.

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 and resource: 'Analyze how EURUSD reacted after historical U.S. CPI releases...' It clearly answers a distinct question ('What happened to EURUSD after historically similar CPI events?') and differentiates from siblings like get_historical_analogs by focusing on reaction statistics rather than just analog identification.

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 gives clear context for when to use the tool: when the agent needs historical post-CPI reaction analysis for EURUSD. It also states scope limitations ('Currently supports US_CPI and EURUSD'). However, it does not explicitly name sibling tools or state when not to use this tool versus alternatives.

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