finance-mcp-server

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

The readOnlyHint and openWorldHint annotations already signal a safe read operation. The description adds meaningful context by disclosing the output includes current price in USD, 24h price change, market cap, and volume, which is useful since no output schema exists. 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?

The description is two sentences, front-loads the main action and return values, then gives concise usage guidance. Every sentence adds value with no wasted words or redundancy.

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 one-parameter read-only tool with no output schema, the description covers purpose, data returned, and use cases. It also implicitly differentiates from sibling tools by focusing on crypto, making it sufficiently complete for an agent to select and 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 description coverage is 100% per context signals, and the coins parameter is already well-documented in the schema with examples. The description's mention of 'multiple coins' slightly reinforces the array semantics but adds no extra detail beyond the schema, so baseline 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 fetches real-time cryptocurrency prices and 24-hour market data for multiple coins, listing specific return fields (USD price, 24h change, market cap, volume). This specific verb+resource combination distinguishes it from sibling tools like get_stock_data and 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?

It provides explicit use cases: 'Use for crypto portfolio tracking, price alerts, or comparing digital assets.' While it doesn't explicitly mention when not to use it or name alternatives, the context makes it clear this is for crypto only, which differentiates it from non-crypto sibling tools.

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?

With annotations already declaring readOnlyHint and openWorldHint, the description still adds value by specifying the return fields: 'exchange rate, bid/ask spread, and last update timestamp.' It also emphasizes 'current' rates, reinforcing the dynamic nature of the data beyond what openWorldHint alone conveys.

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 concise and well-structured, with two sentences that front-load the purpose, then detail the returned data, and finally mention relevant use cases. No unnecessary words or repetition of schema 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?

For a simple read-only lookup tool with one optional parameter and no output schema, the description adequately covers the return fields and context. It could be slightly more specific about which currencies are supported, but 'major world currencies' is sufficient for typical use.

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% and the single parameter 'base' is well-documented in the schema with default 'USD' and examples. The description adds minimal parameter-related meaning beyond 'major world currencies,' but the schema already carries the full weight, 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: 'Look up current foreign exchange rates between major world currencies.' It names the resource (foreign exchange rates), specifies the verb (look up), and differentiates from sibling tools like crypto and stock by emphasizing 'major world currencies.'

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 travel planning, international business transactions, or forex trading decisions.' This gives clear context for when to use the tool, though it does not mention exclusions or directly compare to siblings like get_crypto_prices or get_stock_data.

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 known. The description adds valuable behavioral context by specifying the data source (Yahoo Finance) and the comprehensive list of returned fields (price, 52-week range, volume, market cap, etc.), which helps the agent set expectations without contradicting 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?

The description is two sentences, front-loads the action, and every sentence earns its place. The first sentence states the purpose and source; the second lists return fields and use cases. No fluff or redundancy.

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 read-only tool with no output schema, the description fully covers what data is returned and what it's used for. The annotations cover safety, and the sibling list clarifies scope. Nothing critical is missing.

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 for the only parameter (ticker) is 100%, with a clear description and examples. The tool description adds no extra parameter-specific detail, but the schema already fully documents the parameter, 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 uses a specific verb 'Retrieve' with a clear resource: 'stock market data for individual ticker symbols from Yahoo Finance.' It enumerates the exact data fields returned and implicitly distinguishes itself from siblings like get_crypto_prices and get_exchange_rates by focusing on individual stock tickers.

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 'Use for fundamental analysis, stock screening, or building financial dashboards,' which gives clear context for when this tool is appropriate. While it doesn't explicitly exclude alternatives, the focus on individual tickers and the sibling names make the boundaries evident.

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 tool is known to be safe. The description adds that it 'returns matching ticker symbols with key metrics,' which discloses the return behavior beyond the annotation. It doesn't describe edge cases like empty results, but the annotation lowers the burden.

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 function, and every clause adds value—examples of criteria, return behavior, and use cases. No unnecessary 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?

For a single-parameter screening tool with readOnly annotation and no output schema, the description adequately covers purpose, examples, expected return, and usage contexts. It is sufficiently complete for an agent to decide when and how to invoke it.

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?

The schema has 100% coverage with a description for the 'criteria' parameter, but the tool description enriches it with concrete examples (e.g., {'sector': 'technology', 'market_cap_min': ...}). This adds practical meaning beyond the schema's generic key-value description.

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 'Filter and screen stocks based on financial criteria' with a specific verb and resource. It lists concrete examples (market cap range, sector, P/E ratio, dividend yield, revenue growth) and differentiates from siblings like get_stock_data by focusing on screening rather than single-stock retrieval.

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: 'value investing, growth stock identification, or portfolio rebalancing analysis.' While it doesn't explicitly exclude alternatives or mention sibling tools, this guidance clearly implies when the tool is appropriate.

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 useful output details (price per coin, 24h change, portfolio value, top movers) beyond the annotations, but does not disclose potential limitations such as data delays or coverage of obscure coins. This is adequate but not richly transparent.

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, evenly split between what the tool does and when to use it. It is front-loaded with the primary action and outputs, with no redundant words or repetition of schema details.

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 tool's simplicity (one parameter, no output schema), the description fully covers what the agent needs: it lists the inputs (via schema), the outputs (price, change, summary, movers), and the intended use case. The annotations provide safety and world knowledge, making this complete for a read-only monitoring 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?

The input schema fully documents the 'coins' parameter with descriptions for both the array and its items (e.g., 'BTC', 'ETH', 'ADA', 'USDC'), so the schema carries the semantic weight. The description adds minimal extra meaning beyond the schema, aligning with the baseline for high schema coverage.

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 uses a specific verb ('Monitor') and resource ('portfolio of cryptocurrency holdings'), and clearly distinguishes itself from siblings by emphasizing portfolio-level metrics (value summary, top movers) rather than single-price lookups. It also outlines the specific outputs returned.

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 context for use ('Use for active portfolio management and price monitoring'), which implies the tool is for ongoing portfolio oversight. However, it does not explicitly mention when not to use it or name alternatives like get_crypto_prices, so it lacks explicit exclusions.

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