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longbridge

Official

Screener Search

screener_search
Read-onlyIdempotent

Filter stocks by fundamental and technical indicators across US, HK, CN, SG markets. Use saved strategies or custom conditions to get sorted, paginated results.

Instructions

Screen stocks. market: US|HK|CN|SG (Mode B required; Mode A uses strategy's market). Mode A: strategy_id from screener_recommend_strategies — auto-runs saved strategy. Mode B: conditions=[{"key":"KEY","min":"10","max":"50","tech_values":{}},...]. extra_returns=["key",...] adds display-only columns. sort_by_key: key name to sort by; sort_order: asc|desc (default desc). page: 0-based (default 0). Returns {total, items[]{symbol, name, indicators[]{key, name, value, unit}}}. Fundamental keys: pettm pbmrq roe roa netmargin salesgrowthyoy netincomegrowthyoy marketcap(亿) circulating_marketcap(亿) prevclose prevchg(%) divyld la epsttm netincome(亿) sales(亿) turnover_rate balance(万). Technical keys (call screener_indicators for tech_values schema): macd_day/week rsi_day/week kdj_day/week boll_day/week.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketNoMarket: "US" | "HK" | "CN" | "SG". Mode A: overridden by the market embedded in the strategy; pass any value or omit. Mode B: required — determines which market to screen.
strategy_idNoMode A — Strategy ID from screener_recommend_strategies screeners[].id. The tool auto-fetches the strategy and builds filters. Omit for Mode B.
conditionsNoMode B — Filter conditions as objects, passed directly to the API. Each item: {"key": "KEY", "min": "10", "max": "50", "tech_values": {}} The "filter_" prefix is added automatically to the key if missing. Fundamental keys (pass with or without filter_ prefix): pettm pbmrq roe roa netmargin salesgrowthyoy netincomegrowthyoy marketcap(亿) circulating_marketcap(亿) prevclose prevchg(%) divyld la epsttm netincome(亿) sales(亿) turnover_rate balance(万) Technical indicator keys (tech_values required; call screener_indicators for schema): macd_day/week → {"category":"goldenfork"|"deadcross","period":"day"|"week"} rsi_day/week → {"value_type":"overbought"|"oversold"} kdj_day/week → {"category":"goldenfork"|"deadcross"} boll_day/week → {"category":"breakthrough_up"|"breakthrough_down"}
extra_returnsNoExtra indicator keys to include in each result row (display-only, not used as filters). Same key naming as conditions (filter_ prefix added automatically). Example: ["marketcap", "prevclose", "epsttm"]
sort_by_keyNoIndicator key to sort results by (e.g. "marketcap", "roe"). Defaults to the first condition key. Must be one of the condition or extra_returns keys.
sort_orderNoSort order: "asc" | "desc" (default: "desc")
pageNoPage number, 0-based (default: 0)
sizeNoPage size (default: 20, max: 100)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalNoTotal number of matching securities.
itemsNoResult rows for the current page.
Behavior5/5

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

The description discloses all key behaviors: modes, market restrictions, parameter usage (conditions, extra_returns, sorting, pagination), and the exact return structure '{total, items[]...}'. Annotations already indicate read-only and idempotent, so the description adds valuable context on how the API processes requests.

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

Conciseness4/5

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

The description is organized with a clear purpose first, then markets, modes, and parameter details. While fairly long, each section adds necessary information. Minor redundancy exists (e.g., key lists repeated in description and schema), but overall it is well-structured.

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 the tool's complexity (two modes, 8 parameters, extensive keys, output format), the description covers all aspects: mode selection, parameter behavior, key lists, sorting, pagination, and output structure. It references sibling tools for strategy IDs and technical indicator schemas, leaving no major gaps.

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 description coverage is 100%, but the description adds more: it provides a curated list of fundamental and technical keys, explains the automatic 'filter_' prefix, and gives examples (e.g., 'extra_returns: ["marketcap", ...]'). This aids quick comprehension beyond the 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 opens with 'Screen stocks' and immediately specifies the supported markets and two operational modes. It distinguishes from sibling tools by referencing screener_recommend_strategies for Mode A and providing a different parameter structure for Mode B. This makes the tool's purpose and differentiation clear.

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 two distinct modes (saved strategy vs. custom conditions) and when to use each. It references the strategy source tool (screener_recommend_strategies) for Mode A. However, it could have been more explicit about when not to use this tool compared to other search or filter tools in the sibling list.

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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