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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds real value beyond that: result ordering (newest first) and a derived metric (first-to-last close change %) that the caller could not infer from the schema. It stops short of stating behavior on invalid codes or non-trading days.

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, no filler, with the core purpose front-loaded and the usage cue immediately after. Every clause earns its place.

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 no output schema, the description correctly compensates by describing the return shape (OHLCV rows, newest first) and the appended performance number. Minor gaps remain around error handling and whether weekends/holidays are skipped.

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 coverage is 100% (code format, days default 20 / max 120 are documented there), so baseline 3 applies. The description reinforces 'one stock' and the window semantics of the performance figure but adds no new parameter detail.

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?

Names a specific resource and shape: daily OHLCV history for one Korean listed stock, with an explicit ordering and a computed performance figure. An agent can distinguish this from a snapshot tool like kr_quote, though no sibling is named explicitly.

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 'Use for "how has X performed" questions' gives a positive trigger, but there is no exclusion or alternative routing (e.g. use kr_quote for a current price, kr_index for market-level performance). Usage is implied rather than delimited.

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