premium-data-mcp-server

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

Annotations already declare readOnlyHint and openWorldHint. The description adds context by specifying the mechanism (Google Shopping and URL monitoring), but lacks details on latency, error handling, or data freshness. It provides adequate but not exceptional transparency beyond 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 concise and well-structured: a single sentence stating the core purpose followed by a clear, labeled list of parameters. Every sentence earns its place with no 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?

Given the tool's simplicity (3 parameters, no required params, no output schema), the description covers purpose and parameters sufficiently. It could mention result format or pagination, but overall it is complete enough for standard usage.

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?

With 0% schema description coverage, the description compensates well by explaining each parameter purpose: product_name, product_urls (direct URLs to check), max_results with default. This adds meaningful semantics beyond the schema's bare types and defaults.

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: comparing product prices across e-commerce platforms using Google Shopping and direct URL monitoring. This specific verb+resource combination differentiates it from sibling tools like search_amazon_products, which is platform-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?

No usage guidelines are provided. The description does not indicate when to use this tool over alternatives like search_amazon_products, nor does it mention prerequisites or when not to use it. A user must infer from the name and context.

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 provide readOnlyHint=true and openWorldHint=true, which are consistent with the description. The description adds no additional behavioral context (e.g., rate limits, authentication, or data freshness). Thus, it meets the minimum but does not exceed annotation coverage.

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 paragraph with a bullet-like Args list. It front-loads the purpose and uses no extraneous words, making it highly efficient.

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 description covers the tool's purpose and all parameters. However, lacking an output schema, it could briefly mention the response structure (e.g., records, officers, filings). Still, it is fairly complete for a lookup tool with annotations.

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 0%, but the description's Args section explains each parameter with examples (e.g., jurisdiction codes 'us_de', 'gb') and default behavior. This adds meaning beyond the schema types and defaults.

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 does a lookup of company registration records, officers, and filings from global business registries. This specific verb+resource combination distinguishes it from sibling tools like compare_product_prices or search_amazon_products.

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 purpose is clear, the description does not explicitly state when to use this tool versus alternatives or provide exclusions. The context signals show sibling tools are unrelated, so usage is implied, but no direct guidance is given.

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 indicate readOnlyHint=true and openWorldHint=true. The description adds no behavioral details beyond the stated purpose. It does not discuss rate limits, authentication, result stability, or error states.

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 extremely concise: a single purpose sentence followed by a bullet list for parameters. Every sentence is necessary, and the key action is front-loaded.

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 no output schema, the description hints at returned data (details, pricing, reviews, ratings) but lacks specifics on response format, pagination, or filtering. Adequate for a simple search tool but not thorough.

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 0%, so the description must explain parameters. It does so for all three: search_query (product search query), asins (list of ASINs for direct lookup), and max_results (max results, default 15). This adds meaning beyond the bare 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 searches Amazon for product details, pricing, reviews, and ratings. This specific verb-resource combination distinguishes it from siblings like compare_product_prices (comparison) and lookup_business_registration (business data).

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?

No explicit guidance on when to use search vs. siblings or alternative tools. The description does not mention prerequisites, common queries, or scenarios where other tools are preferred.

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 indicate readOnlyHint=true and openWorldHint=true. Description adds 'Search' verb, consistent with read-only access. No additional behavioral details like rate limits or authentication requirements. Adequate given annotation coverage.

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?

First sentence establishes purpose. Args list is clear and follows standard docstring format. No extraneous information. Slightly verbose with 'Args:' heading when schema already exists.

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?

Describes parameters adequately but omits output structure, pagination behavior, or error scenarios. With openWorldHint, output may vary, but some guidance on typical response format would be helpful. Sufficient for basic 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 has 0% description coverage; description compensates by explaining each parameter (search_term, category, severity, max_results) with brief but meaningful context. Lacks deeper explanation of severity classes or category values.

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 searches FDA recalls, safety alerts, and enforcement actions. Specifies scope across drugs, food, and devices. Distinct from sibling tools which involve product prices, business registration, Amazon products, and government contracts.

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?

No guidance on when to use this tool versus alternatives. Does not mention prerequisites, typical scenarios, or exclusions. Users must infer from context.

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 provide readOnlyHint and openWorldHint. The description adds parameter details but does not disclose additional behavioral traits like rate limits, pagination, or required authentication. 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 a single sentence followed by a list of parameters. It is concise, front-loaded with purpose, and every detail is useful. No superfluous text.

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 description covers parameters well but lacks details on the output format or field schema. Without an output schema, the agent may need more context on what the results contain. The openWorldHint suggests variability, but no specifics are given.

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 0%, and the description compensates fully by explaining all 5 parameters with examples (e.g., 'cybersecurity' for keyword, 'Department of Defense' for agency) and default values, providing clear meaning beyond the raw 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 searches US federal government contracts, grants, and spending data from USASpending.gov. It uses a specific verb and resource, distinguishing it from siblings like search_amazon_products.

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 government spending data through the source and parameter examples. No explicit when-not or alternatives are given, but the context is clear enough to differentiate from siblings.

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