Get capital flow (money flow) analysis for a stock.
Returns intraday flow timeline and breakdown of capital inflows/outflows
by order size: large, medium, and small.
Supported: US stocks, Hong Kong stocks, A-shares.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | ||
| symbol | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the return format (timeline and breakdown) but does not mention behavioral traits like read-only nature, rate limits, or data freshness. Supported markets are stated but other constraints are omitted.
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 efficient: first sentence defines purpose, second details output, third adds supported markets. No redundant information.
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 the tool has 2 parameters, no output schema, and moderate complexity, the description covers the core functionality but lacks parameter explanations and return format specifics. The undocumented 'type' parameter reduces completeness.
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% and description only implicitly covers 'symbol' by mentioning 'a stock'. The 'type' parameter is completely undocumented, leaving the agent without guidance on its meaning or allowed values.
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 returns capital flow analysis for a stock, including intraday timeline and breakdown by order size. It specifies supported markets (US, Hong Kong, A-shares), distinguishing it from siblings like get_intraday or get_kline.
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 implies use for money flow analysis but does not explicitly state when to use this tool versus alternatives like get_market_metrics or get_ticker. No exclusions or prerequisites are provided.
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 data type or operation (e.g., symbol discovery, capital flow, intraday, kline, order book, trades). No two tools have overlapping purposes, and descriptions clearly differentiate them.
All tools follow a consistent 'get_' prefix followed by a descriptive noun (e.g., get_available_symbols, get_intraday, get_kline). No mixing of conventions or vague verb usage.
13 tools is well-scoped for a market data server. Each tool serves a specific need without unnecessary redundancy, covering discovery, real-time, historical, and reference data.
The tool set covers core market data needs: discovery, real-time quotes, historical kline, depth, trades, capital flow, metrics, trading calendar, and sessions. Minor gaps exist (e.g., corporate actions, historical trade list), but the primary workflows are supported.