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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds value beyond annotations by specifying the exact data returned (latest close, changes over 1D/1W/1M/3M/6M/1Y, 52-week range, last ten sessions) and ticker format rules, which helps the agent anticipate behavior.

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?

Two sentences, front-loaded with the core purpose, then specifics, then ticker format. No redundant words; every sentence adds essential 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?

The tool has one parameter and no output schema, so the description carries the burden of explaining return values. It lists all key outputs, making the tool's behavior clear. Minor gaps such as error handling or limitations are acceptable given the simple scope.

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 lists 'ticker' with example values, and schema coverage is 100%. The description enhances this by explicitly stating the formatting rules (US tickers bare, foreign with exchange suffixes like 005930.KS, 6857.T, ASML.AS), providing deeper semantics beyond the schema.

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 the tool reads end-of-day price history for ~2,500 tickers from a data lake, listing specific outputs (latest close, period changes, 52-week range, last ten sessions). It distinguishes itself from siblings by focusing on individual tickers and historical price data, not indices or definitions.

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 context on when to use this tool (for price history of tickers) and the data it returns. However, it lacks explicit exclusion or alternative guidance (e.g., 'for index data, use get_index_snapshot'), 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.