Get current trading session schedule for a stock market.
Returns session begin/end times and session type (pre-market, regular, after-hours, closed, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
| market | 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 provided, so description must fully disclose behavior. It mentions 'current' but fails to state that this is a read-only operation, specify timezone, data freshness, or any implications. Minimal behavioral detail.
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, front-loaded with core purpose. However, it omits parameter details, which would have improved utility without adding length.
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 no output schema and 0% parameter description coverage, the tool context is thin. Missing details on output format, timezone handling, and optional behavior. Adequate only for simplest use case.
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 coverage is 0% for the single parameter 'market'. Description does not mention the parameter at all, leaving the agent to infer its meaning solely from the schema type 'string'. This is a critical gap.
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?
Clearly states verb 'Get' and resource 'trading session schedule' for a stock market. Lists return content (session times and type). Distinguishes from siblings like 'get_trade_days' which returns trading days.
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?
No explicit guidance on when to use this tool versus alternatives. No when-not-to-use or prerequisite conditions mentioned. The description only implies usage for getting current schedule but lacks comparative context.
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.
