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longbridge

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Market Anomaly

anomaly
Read-onlyIdempotent

Detect unusual price and volume changes across HK, US, CN, and SG markets. Optionally filter by stock symbol and control the number of alerts returned.

Instructions

Get market anomaly alerts (unusual price/volume changes). market: HK/US/CN/SG. symbol: optional, filter to a specific stock. count: results per page (default 50, max 100). Returns changes[]{symbol, name, change_rate, volume, ...}, all_off.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketYesMarket code: HK, US, CN, SG
symbolNoFilter to a specific symbol, e.g. "700.HK" or "AAPL.US"
countNoNumber of results to return (default: 50, max: 100)
Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description does not need to emphasize safety. However, it adds return structure (changes array with fields) and mentions 'all_off' without explanation, which is a modest addition beyond the structured fields.

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 brief, using a single sentence for purpose and a list for parameters/return. It avoids unnecessary details but could be more structured (e.g., separate sections for parameters and output). Still, it is appropriately sized for a simple tool.

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

Completeness3/5

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

For a tool with 3 simple parameters and no output schema, the description provides enough to understand basic usage and return format. However, it lacks explanation of 'all_off' and does not describe what constitutes an anomaly, which could be important for agents to interpret results.

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

Parameters3/5

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

Schema description coverage is 100%, so baseline is 3. The description reiterates parameter meanings (market, symbol, count) and adds default/max for count, but this information is already present in the schema descriptions. No additional semantic value.

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 the tool retrieves market anomaly alerts for unusual price/volume changes, with specific market codes and optional symbol/count parameters. It is a specific verb+resource combination that distinguishes it from sibling tools like 'candlesticks' or 'intraday' that 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.

Usage Guidelines2/5

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

No guidance on when to use this tool vs. alternatives such as 'top_movers' or 'market_temperature'. The description assumes the agent knows this tool is for anomaly alerts but does not provide context for selection among similar data retrieval tools.

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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