stock_cyq_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description's burden is lower. It adds the source URL and return type (pandas.DataFrame) but does not disclose potential rate limits, error behavior, or whether the symbol parameter expects a market prefix (despite the URL example 'sz000001'). No contradiction with annotations.

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 compact and follows a docstring format with source URL, parameter definitions, and return type. Every line contributes useful information, though it could be improved by front-loading a one-sentence summary before the technical details.

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?

There is no output schema, so the description's 'return: 筹码分布' is the only return value documentation, lacking column details or behavior for invalid inputs. It covers basic invocation (symbol, adjust) but leaves gaps in data semantics and edge cases, making it adequate but not comprehensive.

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%, but the description compensates by defining both parameters: 'symbol' as stock code and 'adjust' with explicit choices ('qfq', 'hfq', ''). This adds meaningful value over the bare schema, though the exact format for 'symbol' (e.g., 6-digit code vs. with prefix) remains ambiguous.

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 identifies the tool as providing chip distribution (筹码分布) for concept boards in the Eastmoney daily K-line market center, with a source URL and parameter documentation. It clearly names the resource and scope, though it lacks an explicit verb like '获取' or 'query' to indicate an action.

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?

No guidance is given on when to use this tool versus alternatives such as stock_board_concept_hist_em or stock_zh_a_hist. There is no mention of prerequisites, market prefixes, or typical use cases; the description only documents parameters without selection criteria.

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