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

Annotations declare readOnlyHint=true, and the description adds valuable behavioral context beyond that: it details the exact statistical outputs, clarifies the 5-year sampling window, and warns that values are fractional (0.0821 means 8.21%). This helps the agent interpret results correctly without contradicting the read-only hint.

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 three sentences long and every sentence earns its place: listing the outputs, stating the use case, and explaining the fractional notation. No extraneous words or repetition of the name/title.

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?

For a simple read-only tool with one parameter and no output schema, the description is complete: it enumerates the returned metrics, states the historical window, and explains the value format. It provides enough context for an agent to know what to expect and when to use it, without needing an output schema.

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% for the single ticker parameter, which already explains it clearly. The description does not add further parameter semantics, but it doesn't need to. Baseline 3 is appropriate since the schema fully covers the parameter.

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 what the tool does: provides the historical distribution of 5-day and 1-month returns for a ticker over the last 5 years, including mean, standard deviation, percentiles, histogram, and worst drawdowns. It also explicitly frames its purpose ('whether a move is unusual FOR THIS NAME'), distinguishing it from generic market analysis tools like get_composite or get_signal.

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 usage context: 'Use it to say whether a move is unusual FOR THIS NAME rather than in the abstract.' This implies the tool is for ticker-specific historical comparison, but it doesn't explicitly mention when not to use it or name alternative sibling tools. The guidance is sufficient for most intended scenarios.

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