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longbridge

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Rank List

rank_list
Read-onlyIdempotent

Retrieve a ranked stock list by specifying a leaderboard tab key. Get sorted results with metrics like price, change, inflow, and market cap.

Instructions

Get ranked stock list by leaderboard tab key. key: from rank_categories second_tags[].key (e.g. "hot_all-us", "hot_up-hk", "trade_heat-us"). market: inferred from key suffix (-us/-hk) or pass explicitly. size: results (default 20). Returns lists[]{symbol, name, last_done, chg(decimal), inflow, market_cap, pre_post_price, pre_post_chg, amplitude, turnover_rate, volume_rate, five_day_chg, ten_day_chg, twenty_day_chg, this_year_chg, industry, intro}, updated_at.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesTab key from rank_categories second_tags[].key, e.g. "hot_all-us" (US total heat), "hot_up-hk" (HK rising heat), "trade_heat-us" (US hot trades). The "ib_" prefix is stripped from rank_categories keys and added back automatically.
marketNoMarket override: "US" | "HK" | "CN" | "SG". Defaults to the market suffix in the key (e.g. "ib_hot_all-hk" → HK), then "US".
sizeNoNumber of results to return (default: 20)
need_articleNoWhether to include related news articles (default: false)
Behavior5/5

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

Beyond annotations (readOnly, idempotent, openWorld), the description adds key behavioral details: key format with 'ib_' prefix stripping/adding, market inference logic, default size, and the complete list of return fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise, front-loaded with purpose, then details on key, market, size, and return fields. Every sentence adds value without repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description lists all return fields in detail. It covers all parameters and their relationships, making it complete for a data retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with good descriptions, and the description adds context on key format and market inference, enhancing meaning beyond schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get ranked stock list by leaderboard tab key', specifying the verb and resource. It explains the key parameter and its source, distinguishing this tool from siblings like rank_categories.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use the tool (to get ranked lists by key) and how market is inferred, but does not mention when to avoid it or specify alternatives among many siblings.

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

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