Finance MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations (readOnlyHint=true, openWorldHint=true) already establish safety and openness. The description adds the return data details (price, change, market cap, volume), which is useful but not additional behavioral context like rate limits or data freshness. It does not contradict annotations.

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 the main verb and scope. Every sentence earns its place: the first states the action and data scope, the second details outputs and use cases. No wasted 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?

Given the simplicity of the tool (one optional param, no output schema), the description adequately conveys what it returns and why to use it. It lacks mention of what happens with no coins input, but overall it is complete enough for basic invocation.

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 detailed param description ('List of cryptocurrency symbols or names to fetch price data'). The tool description adds only the idea of 'multiple coins' without clarifying behavior when the optional parameter is omitted (required=0), so it adds minimal value beyond the schema.

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's function ('Fetch real-time cryptocurrency prices and 24-hour market data for multiple coins') and specifies the exact output fields (price, change, market cap, volume). This distinguishes it from sibling tools like get_exchange_rates (fiat) and get_stock_data (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?

Provides clear use cases ('crypto portfolio tracking, price alerts, or comparing digital assets') that signal appropriate contexts. However, it does not explicitly mention when not to use it or how it differs from the sibling track_crypto_portfolio, so it lacks exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds context about return data (bid/ask spread, timestamp) and the 'current' nature of rates, but does not mention data source, refresh rate, or limitations. This matches the calibration baseline of 3.

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 two sentences, with the first sentence front-loaded with the purpose and the second adding return details and use cases. Every word earns its place, making it highly concise and well-structured.

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?

For a simple tool with one optional parameter and no output schema, the description is complete: it states what it does, what it returns (key fields), and when to use it. No critical information is missing for a read-only lookup 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% (the only parameter 'base' is fully described). The tool description does not add any additional parameter meaning beyond the schema, so the baseline of 3 is appropriate.

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's function with a specific verb ('Look up') and resource ('current foreign exchange rates between major world currencies'). It also lists the return fields, distinguishing it from sibling tools focused on crypto and 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 provides explicit use cases (travel planning, international business, forex trading) which imply when to use the tool. However, it does not explicitly name alternatives or state when not to use it, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds the data source (Yahoo Finance) and scope (individual ticker symbols) but does not disclose other behavioral aspects like rate limits, data latency, or error handling. This adds some value but not rich context.

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 two sentences plus a short use-case sentence. It is front-loaded with the main purpose, lists useful data fields, and provides guidance. Every sentence earns its place without unnecessary verbosity.

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 no output schema, the description compensates by listing the specific data fields returned. It covers purpose, data content, and use cases. It could mention single-ticker limitation or potential errors, but for a simple one-parameter tool, it is quite 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?

Schema coverage is 100% with a well-described ticker parameter including examples. The description does not add additional parameter semantics beyond confirming it handles individual ticker symbols. Baseline of 3 is appropriate given the schema handles the parameter documentation.

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 retrieves comprehensive stock market data for individual ticker symbols from Yahoo Finance. It lists specific data fields, distinguishing it from siblings like get_crypto_prices or get_exchange_rates.

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 provides explicit use cases: 'Use for fundamental analysis, stock screening, or building financial dashboards.' It does not explicitly state when not to use it (e.g., for crypto or exchange rates), but the individual-ticker focus and sibling names imply this.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, so the description adds modest value by stating it 'Returns matching ticker symbols with key metrics.' It does not disclose additional behavioral traits like pagination, result limits, or matching logic, but given the read-only annotation the bar is lower and the description is adequate.

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 two sentences with no filler. It front-loads the core action ('Filter and screen stocks'), then lists criteria, return value, and use cases efficiently. Every sentence earns its place.

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?

For a single-parameter tool with no output schema, the description covers the main aspects: what it does, what it returns ('matching ticker symbols with key metrics'), and when to use it. Minor gaps include not clarifying whether criteria is optional and what exactly constitutes 'key metrics,' but overall it is complete enough for an 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% for the single 'criteria' parameter, so baseline is 3. The description adds examples of filter attributes (e.g., dividend yield, revenue growth) but does not provide syntactic details beyond the schema's own example. It enriches the semantic picture slightly but does not fully compensate for the lack of structured parameter definitions.

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 opens with a specific verb phrase 'Filter and screen stocks' and enumerates concrete criteria like market cap range, sector, P/E ratio thresholds, dividend yield, and revenue growth. It clearly distinguishes from siblings like get_stock_data by implying batch screening across stocks rather than retrieval of a single stock.

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 provides clear usage context with 'Use for value investing, growth stock identification, or portfolio rebalancing analysis.' It does not explicitly name alternatives or state when not to use it, but the use cases effectively guide the agent toward this tool over siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, covering the safety profile. The description adds behavior details: real-time data and specific output metrics (price, 24h change, portfolio value, top movers). However, it does not disclose limitations like data source reliability, rate limits, or behavior for invalid symbols.

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 two sentences, front-loaded with the core action and outputs. Every sentence earns its place with no redundancy or filler.

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 simple one-parameter schema and no output schema, the description adequately covers the return values and use case. It lists the specific outputs (current price, 24h change, portfolio value, top movers), making it complete for this level of complexity.

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 the 'coins' parameter clearly documented as cryptocurrency symbols. The description adds no additional parameter semantics beyond reinforcing the portfolio context, so the baseline of 3 is appropriate.

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 specifies the tool's function: monitoring real-time cryptocurrency portfolio prices and performance metrics. It differentiates from sibling tools like get_crypto_prices by emphasizing portfolio-level outputs such as value summary and top movers, not just individual prices.

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?

Explicitly states 'Use for active portfolio management and price monitoring', providing a clear use case. However, it does not contrast with alternative tools like get_crypto_prices or mention when not to use it, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.