Market Intel MCP

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

No annotations provided, so description carries full burden. It mentions 'snapshot' and 'via Coinbase' but lacks details on data freshness, update frequency, or any rate limits. It does not contradict annotations since none exist.

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, no wasted words. Information is front-loaded: snapshot, source, and use case.

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 2 parameters fully described in schema and no output schema, the description provides enough context for use. However, it could benefit from mentioning return structure or field details for screening purposes.

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 both parameters having descriptions in the schema. The description adds no extra information about parameters beyond what the schema provides.

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?

Description clearly states it provides a snapshot of major cryptocurrencies with current USD prices from Coinbase. It specifies the verb (snapshot), resource (major cryptocurrencies), and data (current USD prices). It distinguishes from siblings like crypto_price or stock_quote by focusing on market overviews.

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 says 'Use for market overviews and screening', giving a clear context of use. However, it does not mention when not to use it or alternative tools like crypto_price for specific coin details.

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?

No annotations are provided, so the description carries full burden. It discloses data source (Coinbase), currency scope (USD by default), and input format (comma-separated symbols). It does not mention rate limits, error handling, or data freshness, but for a simple price tool these are minor omissions.

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 exactly convey purpose, input, and use cases with no wasted words. Front-loaded with the core action.

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 tool has no output schema, so the description could mention return format. However, the context is sufficient for a straightforward price lookup. It covers what, how, and when to use, lacking only explicit error/edge-case description.

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%, so the schema already clearly defines both parameters. The description adds minimal extra meaning beyond what the schema provides (e.g., example symbols). 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 states 'Current USD price for one or more cryptocurrencies, by symbol... via Coinbase.' It clearly specifies the verb (get price), resource (cryptocurrencies), and scope (one or more, by symbol). It differentiates from siblings like stock_quote and fx_rates by explicitly naming crypto and Coinbase.

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 says 'Use for crypto research, portfolio checks, or answering "what's X trading at?"' providing clear when-to-use guidance. While it doesn't mention when not to use, the sibling list implies alternatives for other asset types.

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?

No annotations are provided, so the description must cover behavioral traits. It mentions 'latest ECB reference rate via Frankfurter' but does not disclose potential limitations (e.g., daily updates, unsupported currencies, error behavior) or side effects. The description adds minimal value beyond the obvious conversion action.

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 consists of two concise sentences with no extraneous information. It front-loads the core action and source in the first sentence, then adds the use case in the second. However, it could be slightly more structured (e.g., listing key points).

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 tool has three parameters and no output schema, yet the description does not explain the return format (e.g., just the converted amount or a full object) or error handling. Given the presence of a sibling fx_rates, the description could clarify the differentiation. The description is incomplete for a tool with no annotations or output schema.

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 has 100% description coverage, so the description does not need to add much parameter detail. It does provide context about the rate source ('ECB reference rate via Frankfurter') but does not clarify parameter values beyond what the schema already states (e.g., currency codes, amount default).

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 action (convert an amount between two currencies) and the resource (latest ECB reference rate via Frankfurter). It explicitly mentions the use case (currency conversion and pricing) and distinguishes it from sibling tools like crypto_market, crypto_price, fx_rates, and stock_quote, which handle different asset types or operations.

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 says 'Use for currency conversion and pricing,' which provides a clear usage context but does not specify when not to use this tool or contrast it with alternatives like fx_rates (which may be for retrieving rates without conversion). The guidance is implied rather than explicit.

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 no annotations, the description partially compensates by noting the data source and that rates are 'latest', but fails to mention side effects (none expected), update frequency, or authorization needs. It is adequate but not rich.

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 cover purpose, source, and behavior with no redundancy. Every word adds value.

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 tool with no output schema, the description gives enough context (source, scope) to use it effectively. Missing details on output format are minor given the straightforward nature.

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 clear descriptions for both parameters. The description adds value by explaining the source (ECB) and that rates are returned for all or selected targets, going 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 provides latest FX rates for a base currency, specifies the data source (ECB via Frankfurter), and distinguishes from sibling fx_convert (which does conversions). The verb 'returns' and scope 'all or selected' are specific.

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?

While the description implies use for fetching current rates, it does not explicitly state when to prefer this over siblings like crypto_market or fx_convert. No guidance on prerequisites or alternatives is provided.

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 no annotations, the description carries full burden. It discloses the data source (Yahoo Finance) and return fields but omits details like data freshness, rate limits, or error handling.

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 three sentences long, front-loaded with the main purpose, and contains no unnecessary wordiness.

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 quote tool without an output schema, the description adequately explains what is returned. It could mention potential errors or data delays but is complete enough 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% with a clear parameter description. The description adds further context with examples (AAPL, MSFT, ^SPX) and explains symbol formats, providing extra 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 retrieves the latest quote for stocks, ETFs, or indices, listing specific return fields and examples. It distinguishes from sibling tools focused on crypto and forex.

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 says 'Use for equity research,' providing context. It does not include explicit when-not scenarios but the sibling tools implicitly differentiate asset classes.

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