seo-web-analysis-mcp-server

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

Annotations declare readOnlyHint=true, and the description adds that the tool returns A, MX, CNAME, NS, and TXT record details, giving the agent an accurate picture of the output. It doesn't mention rate limits or failure modes, but for a simple read-only DNS lookup, the provided context is sufficient.

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: the first states the action, the second lists use cases. No wasted words, key information 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?

A single-parameter read-only tool with no output schema; the description sufficiently covers what the tool does, what it returns, and when to use it. No major gaps.

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 already fully documents the 'domain' parameter with examples (100% coverage). The description adds no additional parameter-level detail, so it meets the baseline of 3.

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 a specific verb 'Perform DNS lookup' and a resource 'domain', and enumerates the record types it returns. This clearly distinguishes it from sibling tools like lookup_whois or check_ssl.

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 explicitly lists use cases: 'email setup verification, DNS troubleshooting, or server infrastructure research.' While it doesn't name alternative tools, the use cases are specific enough to guide selection.

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 doesn't need to emphasize safety. It adds valuable behavioral context by detailing exactly what the tool inspects and returns (issuer, expiration, SANs, key strength, chain status), which goes beyond the basic annotation. However, it does not mention potential network timeouts or rate limits, but given the read-only nature and existing annotations, this is sufficient.

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, containing two sentences: the first states the function and return content, the second lists use cases. Every sentence earns its place with no redundancy or 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?

For a simple single-parameter tool with no output schema, the description fully explains what the tool does and what it returns. It covers purpose, return values, and typical use scenarios, making it complete enough for an agent to decide to use it and understand outcomes.

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 already provides a complete description of the 'domain' parameter with an example, so schema coverage is 100%. The description does not add extra parameter-level details beyond what is in the schema, landing at the baseline of 3.

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 'Inspect SSL/TLS certificate details for a domain' with a specific verb and resource, and lists concrete return details like issuer, expiration, SANs, key strength, and chain validation. This distinguishes it from sibling tools like check_dns or lookup_whois which target different resources.

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 security audits, certificate renewal tracking, or compliance verification.' It suggests when to use the tool but does not mention when not to use it or explicitly reference alternative sibling tools, 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 and openWorldHint=true, lowering the burden on the description. The description adds behavioral context by noting it extracts from 'all accessible pages' and listing the specific return fields, which goes beyond simple operational safety. It does not fully disclose crawler limitations or rate-limiting, but with annotation coverage, this is acceptable.

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 primary action, and every clause adds value. It efficiently conveys purpose, output, and use cases with no redundant or vague phrasing.

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 moderate complexity (2 params, no output schema), the description covers its purpose, output, and use cases adequately. It lacks minor details such as explicit mention of crawl limits or domains, but these are partially addressed in the schema and annotations, so overall it is sufficiently 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% for both parameters, and the descriptions in the schema are clear. The tool description does not add additional parameter-level meaning beyond what the schema already provides, so a baseline score 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 ('Crawl') and resource ('a website'), and enumerates the extracted data (titles, meta descriptions, headings, body text, links, page structure). This differentiates it from sibling tools focused on DNS, SSL, tech stack, and WHOIS.

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 contexts for use ('SEO audits, content inventory, site mapping, or data extraction for analysis'), but does not explicitly mention when not to use it or name alternative tools. This is clear context without exclusions, fitting a score of 4.

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, and the description adds value by specifying what will be returned (framework names, CMS, analytics, etc.). It does not contradict the annotations. This is sufficient for a read-only detection tool.

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 primary action and return value. No extraneous content; every clause 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 tool with one simple parameter and no output schema, the description is complete: it states input, output categories, use cases, and the read-only nature. No significant gaps remain.

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 already covers 100% of parameters with a clear description for 'url'. The tool description does not add any additional semantics beyond what the schema provides, meeting the baseline of 3 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 the specific verb 'Identify' with resource 'technology stack and services used by a website', and enumerates the detected categories (frameworks, CMS, libraries, etc.). This clearly distinguishes it from sibling tools like check_dns or check_ssl, which focus on different technical aspects.

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 cases: 'Use for competitive analysis, vendor intelligence, or understanding site architecture.' While it doesn't mention when not to use or name alternatives, the stated context is clear and the division of labor among siblings is obvious.

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 read-only nature is known. The description adds useful detail about the returned data (registrant, registrar, dates, etc.), but does not disclose potential limitations like privacy redaction or rate limits. This is adequate but not richer than annotations alone.

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 that are concise and front-loaded: the first states the purpose, the second lists returned fields 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?

With a single parameter, no output schema, and good annotations, the description sufficiently covers purpose, return contents, and use cases. It lacks caveats about WHOIS privacy or rate limits, but these are not essential for a simple query 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 has 100% coverage with a clear description and example for the 'domain' parameter. The description does not add extra parameter-level detail beyond the schema, so the baseline of 3 applies.

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 ('Query WHOIS database') and resource ('domain registration details'), and lists specific return fields. It effectively differentiates from sibling tools like check_dns, check_ssl, crawl_website, and detect_tech_stack by focusing on WHOIS specifically.

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 ('domain research, owner identification, or tracking registration status'), offering clear context for when to use the tool. It does not explicitly name alternatives or exclusions, but the use cases sufficiently imply usage boundaries.

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