get_agent_statsReturn aggregate 7/30-day MCP usage, fixed client families, tool mix and reliability. Initializations are not unique users; no IP, user-agent, version, arguments, prompts or responses are stored.
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No arguments | |||
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate safe read-only behavior. The description adds value by detailing what data is not stored (no IP, user-agent, etc.), enhancing transparency without contradiction.
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 concise two sentences that front-load the action and essential details, with no unnecessary words.
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?
The description, together with annotations and output schema, covers the tool's purpose and constraints. It lacks mention of update frequency or caching but is otherwise complete.
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?
With zero parameters, the description appropriately focuses on the tool's output and behavior. No additional parameter information is needed.
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 aggregate 7/30-day MCP usage, fixed client families, tool mix, and reliability. It specifies what is included and what is not stored, distinguishing it from sibling tools like get_data_quality or get_confluence_methodology.
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 usage for obtaining aggregate statistics and clarifies privacy aspects (no IP, user-agent, etc.), but does not explicitly contrast with sibling tools or state when not to use it.
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 have distinct purposes, but there is potential confusion between get_confluence_signals and get_signal_history (both dealing with signals) and between get_fund and get_stock (both about holdings). Descriptions help clarify, but minor overlap remains.
All tool names follow a consistent verb_noun pattern (e.g., get_fund, list_funds, preview_watchlist) and use snake_case throughout, making them predictable and easy to understand.
With 13 tools, the server is well-scoped for its domain of 13F filings and research. Each tool serves a clear function, and the count is neither too sparse nor overwhelming.
The tool set covers key operations like listing funds, getting holdings, signal history, and quality warnings. However, it lacks a tool for searching tickers or funds by name, which could be a minor gap for some use cases.