Use this when the user asks for closed trade history of a specific trader.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number | |
| limit | No | Results per page | |
| source | No | Exchange | binance |
| traderId | Yes | The trader ID |
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | Closed positions, most recently closed first | |
| pagination | No |
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?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds the important scope 'closed trade history' but does not disclose pagination behavior, result ordering, or any potential data freshness limitations. With annotations, this is an average but acceptable level.
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 a single, front-loaded sentence that directly states the use case. There is no redundant phrasing, filler, or unnecessary repetition of 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?
With full parameter documentation, clear annotations for identity and safety, and an output schema present, the description adequately complements the structured data. The use-case sentence is sufficient for an agent to competently decide and call this tool.
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 100%, with each parameter already clearly described ('traderId', 'page', 'limit', 'source'). The description does not add any parameter-level nuance beyond the structured schema, so it does not elevate above the baseline.
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 identifies the tool's purpose as retrieving closed trade history for a specific trader, which distinguishes it from siblings like get_positions or get_trader_profile. It lacks an explicit verb such as 'get' or 'returns', but the use-case phrasing makes the intent unambiguous.
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 when to use the tool: 'when the user asks for closed trade history of a specific trader.' This provides clear context for selection, though it does not mention alternatives or explicitly state when not to use it, such as for open positions.
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.
Most tools are clearly distinct, targeting different data categories (market data, signals, traders, account). Some potential overlap exists between get_price, get_candles, and get_market_stats, but their descriptions clarify the specific use cases. Overall, an agent can differentiate them reliably.
All tools follow a consistent verb_noun pattern with the verb 'get' and a descriptive noun (e.g., get_candles, get_signals, get_trader_profile). This uniform naming makes it very predictable for an agent.
With 15 tools, the count is within the ideal range for a domain-specific server. Each tool serves a distinct purpose related to market data, signals, and trader analytics, and none feel redundant or extraneous.
The tool set covers core read operations for market data, signals, traders, and account info, which aligns with the apparent purpose of a data-provider server. Minor gaps include lack of write operations (e.g., placing trades) or historical signal details beyond individual IDs, but these are not critical for a data-oriented service.