Market Eyes Live - stock ratings and mortgage-rate context

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

No annotations provided. Description notes 'free public data' but does not disclose auth needs, rate limits, or side effects. For a read-only tool, basic safety context is missing.

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?

Single focused sentence with key details front-loaded. Efficient but could be slightly more 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?

Explains comparison output metrics but does not specify return format or scope (current vs historical). Adequate given no 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?

Single parameter 'symbols' fully described in schema (100% coverage). Description adds example but no extra semantics beyond 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?

Clear verb 'compare' and resource 'stocks or ETFs' with specific metrics listed. Not explicitly differentiated from sibling get_stock_rating, but purpose is distinct.

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?

Implies usage for comparing 2-5 stocks on MELANY ratings, but no explicit when-not-to-use or alternatives to sibling get_stock_rating.

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 fully disclose behavior. It notes the data is from Market Eyes Live and is free public data, and mentions a personalized signal is available elsewhere. However, it does not specify operational details such as authentication, rate limits, data freshness, or whether the operation is read-only (likely but not stated).

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, each serving a clear purpose: stating what data is returned, listing example use cases, and noting the data is free. It is front-loaded with the core function and contains no fluff.

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?

Without an output schema, the description gives a sufficient overview of the return content (treasury yield, MBS momentum, rate environment). While it does not specify the exact format or structure, the listed data points and examples provide enough context for an agent to understand the tool's output.

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 tool has zero parameters, and the schema coverage is 100% (no parameters to cover). Per guidelines, this gives a baseline of 4. The description adds value by explaining what the output includes, which compensates for the lack of parameter details.

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 current U.S. mortgage-rate context, specifying three key data points (10-year Treasury yield, MBS momentum, rate environment). It includes example questions that directly relate to mortgage rates, distinguishing it from sibling tools which focus on 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 example use cases ('should I lock my mortgage rate today', etc.) that illustrate when to use the tool. It does not explicitly exclude scenarios or mention alternatives, but the context of sibling tools (stock-related) makes the intended usage clear.

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 bears full responsibility. It discloses the detailed output format and the source (Market Eyes Live), making the behavior transparent. However, it does not explicitly state side effects (none expected) or error conditions, but for a read-only retrieval, this 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 a single, well-structured sentence that front-loads the core purpose and efficiently lists all returned data without extraneous words. Every phrase 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?

Given the tool's simplicity (one required parameter, no output schema), the description sufficiently explains the return content and source. Missing details on error handling or limitations are minor, but overall it provides a complete picture for an agent to use 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?

The schema covers 100% of parameters (symbol defined with example tickers). The description adds context by specifying 'U.S. stock or ETF' and the examples (NVDA, AAPL, VOO), which enriches the parameter meaning beyond the schema's generic 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's purpose: retrieving MELANY's data-driven rating for a single U.S. stock or ETF, and enumerates the specific outputs (conviction tier, composite score, factor scores, risks, theme context). It distinguishes from siblings by its focus on a single stock rating, as siblings compare stocks or provide mortgage context.

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 getting a rating for an individual stock but does not provide explicit guidance on when to use this tool versus alternatives like compare_stocks. There is no mention of when not to use it or any prerequisites.

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