Free analysis of a US-listed ETF. Scores the fund against Stoxly's 10-point checklist (expense ratio, fund size, fund age, number of holdings, top-10 weight, top sector weight, volatility, 1/3/5-year returns) and returns the score, a descriptive verdict, every metric value and a link to the full analysis page.
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | Ticker symbol in Yahoo Finance format, e.g. AAPL, BRK-B, SAP.DE, VOO |
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?
With no annotations, the description carries the full burden. It discloses that the tool scores against a 10-point checklist and returns the score, verdict, all metric values, and a link. This is clear behavioral context, though it does not explicitly state the absence of side effects (e.g., read-only nature).
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, information-dense sentence that front-loads the core purpose and then efficiently lists the checklist and output components. No unnecessary words or repetition.
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 absence of an output schema, the description thoroughly explains what the tool returns: score, verdict, every metric value, and a link. It also covers the tool's scope (US-listed ETF) and the exact evaluation criteria, making it complete for an AI agent to invoke correctly.
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 100% with a clear description of 'symbol' as a Yahoo Finance ticker. The tool description adds the important restriction that the symbol must be a US-listed ETF, which goes beyond the schema's examples and clarifies valid parameter usage.
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 'Free analysis of a US-listed ETF' and enumerates the specific scoring checklist and return values. This distinguishes it from sibling tool analyze_stock by explicitly targeting ETFs rather than stocks.
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 US-listed ETFs, which helps select this tool over analyze_stock, but it does not explicitly mention when not to use it or name the alternative. The guidance is inferred rather than stated.
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.
The two tools are clearly separated by asset class: ETFs vs. stocks. Descriptions explicitly state the type of security each analyzes, leaving no ambiguity about which tool to use.
Both tools follow a consistent 'analyze_<asset>' naming pattern. This is a predictable and uniform convention.
With only two tools, the server is on the borderline of being too thin. However, the narrow scope of providing security analysis makes the count acceptable, though not substantial.
The tools cover the core analysis functions for stocks and ETFs, returning detailed metrics. A minor gap is the lack of a tool to determine the asset type from a symbol, which could cause friction in workflows.
