lianban-a-share-review

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

No annotations provided, so description bears full burden. It lists returned data categories and mentions optional date parameter but omits behavioral details like authentication, rate limits, or side effects. The tool is read-only, but this is inferred rather than stated.

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 one moderately long sentence but packs significant detail concisely. It front-loads the purpose and then lists KPIs. Could benefit from bullet points for clarity, but overall efficient.

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?

Despite lacking output schema, the description enumerates return components (KPIs, ladder, topics, AI text) adequately for an agent to anticipate results. Complexity is low (single optional param, no nesting) and coverage is sufficient.

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% with thorough description. The tool description reiterates the date default behavior but adds no new parameter semantics beyond citation note, which is not parameter-specific. Baseline 3 is appropriate.

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 complete A-share daily review data, listing specific KPIs and components (limit-up/down, consecutive boards, etc.). It distinguishes itself from siblings by focusing on aggregated market review rather than individual stock history, LHB, or trade date listings.

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?

Provides implicit guidance: omitting date returns latest trading day, and earlier history should be obtained via website/opendata. However, it does not explicitly compare with sibling tools or state when not to use it.

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

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

No annotations provided, so description carries full burden. Adds behavioral context like units (yuan) and citation requirement, but does not explicitly state read-only nature or idempotency. Adequate but not thorough.

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?

Description is reasonably concise, covering core functionality, fields, units, and citation in a few lines. Not overly verbose, but front-loads the main purpose.

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?

No output schema, but description lists all returned fields explicitly (code, name, gain, etc.) and notes units. Provides sufficient context for a simple list tool, though lacks details on ordering or pagination beyond the top parameter.

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% with detailed descriptions for both parameters (top, date). Description adds the unit '元' which is not in schema, but otherwise does not significantly augment parameter meaning beyond 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?

Description clearly states the tool retrieves the 'Dragon and Tiger List' for A-shares on a given trading day, listing fields returned. It differentiates from siblings implicitly (specific data type), but does not explicitly contrast with them.

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 on when to use this tool versus siblings (get_daily_review, get_stock_history, list_trade_dates). Does not mention prerequisites or typical use cases.

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

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

The description discloses that only stocks with records this year are included and requires citation, but lacks details on authentication, rate limits, or behavior for stocks without records. No annotations are provided to compensate.

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 (three sentences) and front-loaded with the main purpose. The citation instruction adds necessary usage context but could be separated for clarity.

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 description covers the tool's data scope and input, but fails to describe the output structure. Without an output schema, agents lack details on returned fields, making it incomplete for complex historical data queries.

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% with a clear description in the schema. The tool description restates the same input formats (6-digit code or Chinese name), adding no additional semantic value 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 retrieves limit-up history and dragon-tiger board history for a stock, specifying input as code or name. However, it does not differentiate from sibling tools like get_lhb, which may also provide similar data.

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 on when to use this tool versus alternatives. The description only notes that it covers records from the current year, which is a limitation but not a usage directive.

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

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

No annotations provided, so description must cover behavior. Mentions descending order, approximate count (30), and limit default. Does not detail error behavior, exact output format, or limit validation, but adequate for a simple list tool.

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?

Extremely concise single sentence with a useful note about earlier history. No unnecessary words, well front-loaded.

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 one optional param and no output schema, description is fairly complete: explains purpose, usage context, limitation. Could add output format (e.g., YYYY-MM-DD), but overall sufficient.

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 has 100% coverage (limit described with default and upper bound). Description adds value by specifying the approximate window size (~30) and reinforcing default, enhancing understanding beyond 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?

Description clearly states it lists A-share trading dates in descending order, about 30 recent ones, and specifies it is intended for use with get_daily_review/get_lhb date parameter, distinguishing it from sibling tools.

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?

Explicitly tells to use output for date parameters of get_daily_review/get_lhb, and provides alternative for earlier history via webpage and open data. Lacks explicit 'when not to use' but is clear for the tool's simplicity.

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