get_kline

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

No annotations are provided, so the description must bear the burden of disclosing behavioral traits. It mentions historical data but fails to describe rate limits, data freshness, error handling, or any limitations. The description adds little beyond the basic purpose.

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 concise with only two sentences covering both languages. It is front-loaded with the core purpose. However, it could be more structured (e.g., listing use cases or parameter hints) to improve scanability.

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?

Given no output schema and no annotations, the description covers the tool's purpose and periods but lacks important details like return format (e.g., OHLCV fields) and whether data is adjusted. This is a moderate gap for a historical data tool that an AI agent needs to effectively use.

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 low (33%: only code has a description). The description repeats the period enum values already in the schema but does not explain the meaning of limit (e.g., number of trading days or bars) or provide examples. It adds no new semantic information beyond what the schema already conveys.

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 retrieves historical K-line data for individual stocks, specifying supported periods (daily, weekly, monthly, intraday) and listing use cases like trend analysis and backtesting. It is distinct from sibling tools such as get_stock_quote or main_fund_rank, which serve different purposes.

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 implies usage for technical analysis and backtesting but does not explicitly state when to use this tool versus alternatives (e.g., get_stock_quote for real-time quotes). No exclusions or complementary tools are mentioned, leaving guidance minimal.

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