Screen the Beijing Stock Exchange (BSE) — China's small-and-medium-enterprise (SME) board.
Args: criteria: filter dict (sector, market cap, etc.) limit: max rows to return
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| criteria | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. The description adds no additional behavioral traits beyond being a screening/filter operation, which is consistent 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?
Two sentences with no fluff. The purpose is front-loaded in the first sentence, and parameter explanations are brief but sufficient.
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?
For a 2-parameter tool with annotations, the description covers both parameters adequately. No output schema exists, so the lack of return value description is acceptable; the tool is straightforward and screening output is implied.
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%, so the description bears the burden. It explains criteria as a filter dict with examples (sector, market cap) and limit as max rows, adding meaningful interpretation beyond the raw 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 it screens the Beijing Stock Exchange (BSE) and identifies it as China's SME board. This specific verb+resource combination distinguishes it from the many sibling tools targeting other exchanges.
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?
The description explicitly states the target market (BSE SME board), providing context for when to use this tool. However, it does not include explicit when-not-to-use or alternative recommendations, though sibling names imply exchange-specific usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct geographic exchange, with no overlap in markets screened. The descriptions specify the exchange and indices, making it easy for an agent to select the correct tool for a given country.
All tools follow the exact same naming pattern: 'screen_<country>_<exchange>' in snake_case, providing a clear and predictable structure. There are no deviations or mixed conventions.
26 tools is on the high side, but appropriate for a global equities screener covering many countries. Each tool serves a distinct market, so the count is justified by the breadth of coverage.
The set covers most major global equity markets, including US, China, India, Japan, and many others. However, some notable markets like Russia or some European exchanges are missing, and there is no tool for screening ETFs or indices directly.