search_stock

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds behavioral context beyond annotations: it warns against code guessing, explains the consequence of wrong codes (wrong stock returned), and notes that multiple matches require user confirmation. This is valuable behavioral disclosure that annotations don't provide.

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 well-structured and front-loaded: the purpose is stated first, then usage guidance, then parameter details. It uses formatting (⚠️, Args, Returns) to improve scannability. It is slightly longer than strictly necessary but every sentence earns its place—the warning about guessing and the multi-match confirmation note are both important.

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 one-parameter lookup tool with rich annotations and an output schema, the description is nearly complete. It covers purpose, usage, parameter semantics, and return behavior (matching list, need for user confirmation). The only minor gap is not describing the exact structure of the returned list, but the output schema likely covers that, and the description explicitly mentions the return type.

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 0%, so the description must compensate. It does: it explains the 'query' parameter accepts Korean/English stock names or 6-digit codes, and provides concrete examples ('알멕', 'Samsung', '005930'). This adds meaning beyond the bare schema, though it could be slightly more exhaustive about edge cases (e.g., partial names).

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's purpose: Korean stock name/code lookup. It specifies the resource (Korean stocks), the action (search/lookup), and explicitly distinguishes itself from the generic 'search' tool by noting it is an alias for 'search' with a clearer name for stock/ticker/종목 keyword matching. This is a specific verb+resource that differentiates it from siblings.

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 explicit when-to-use guidance: call this tool first when you have a stock name but not the 6-digit code, and explicitly forbids guessing codes. It also warns that using wrong codes in other tools (get_price, get_chart) will return wrong stocks. This clearly routes the agent to the correct tool and away from alternatives.

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