Domain & Company Intel MCP

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

No annotations are present, so the description carries full burden for behavioral transparency. It discloses that the tool uses an external API (Cloudflare DNS-over-HTTPS) and returns specific record types. However, it omits details like rate limits, error handling (e.g., domain not found), or whether it makes network requests. The behavior is partially transparent but lacks comprehensive disclosure.

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 at three sentences. The first sentence states the action and method, the second lists return types, and the third provides usage examples. No filler or redundant information. Information is front-loaded and every sentence serves a purpose. Ideal structure.

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 partially compensates by listing the record types returned. However, it does not describe the output format (e.g., whether results are groups by type, or include TTL values). For a simple lookup tool, the information is sufficient for most use cases, but a bit more detail on output structure would make it 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 description coverage is 100% (both 'domain' and 'types' have descriptions in the schema). The tool description adds no further semantic meaning beyond the schema; it mentions record types in the general description but does not elaborate on parameter usage. With full schema coverage, a score of 3 (baseline) is appropriate as the description does not degrade or enhance parameter understanding.

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: 'Look up DNS records for a domain'. It specifies the method (Cloudflare DNS-over-HTTPS) and lists the record types returned (A, AAAA, MX, NS, TXT, CNAME, SOA). This differentiates it from sibling tools like domain_intel (broader intelligence) or email_deliverability (email specific), making the purpose unambiguous.

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 usage context: 'Use to see where a domain is hosted, who runs its mail and DNS, and what verification/policy TXT records it publishes.' However, it lacks explicit guidance on when not to use this tool or alternatives. For example, it does not mention that detailed mail or hosting investigation might better be served by sibling tools. The usage hints are implied but not prescriptive.

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 lists the output fields and mentions RDAP/WHOIS but does not disclose potential limitations (e.g., unregistered domains, rate limits, or non-destructive nature). Minimal but adequate for a read-only information 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?

The description is two sentences, front-loading the purpose and output in the first sentence and usage in the second. No unnecessary words, making it quick for an agent to parse.

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 simple input (one string param) and no output schema, the description covers the returned fields adequately. However, it omits details about date formats or error handling, which a complex agent might need. Still, it's sufficient for most use cases.

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 single parameter. The description adds a clarifying example ('stripe.com') and constraint ('no scheme'), which goes beyond the schema's description. This provides sufficient guidance for correct parameter usage.

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 registration intelligence for a domain via RDAP, listing specific data returned (registrar, dates, EPP codes, etc.). It distinguishes from sibling tools like dns_lookup and tech_stack by focusing on domain registration information.

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: 'vet a company, assess a lead, or judge how established a domain is.' While it doesn't explicitly state when not to use or compare to siblings, the context is clear enough for most scenarios.

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 what the tool returns (MX, SPF, DMARC, provider type, verdict) but does not mention potential behaviors like rate limiting, idempotency, or that it performs external DNS queries. Since it's a simple assessment, the disclosure is adequate but not comprehensive.

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 what the tool does and returns, and ends with usage advice. Every sentence provides essential information with no redundancy or 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?

Given the tool's simplicity (single param, no output schema, no nested objects), the description adequately covers inputs, outputs, and usage. It could explicitly mention that only the domain part of an email is checked, but it's implied. The description is complete for its complexity.

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%, so baseline is 3. The description adds value by clarifying that the parameter can be a domain or email address and that it extracts the domain for email addresses. This goes beyond the schema description, which only states 'A domain (stripe.com) or an email address (a@stripe.com)'.

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 specifies the tool's purpose: assessing mail deliverability and sender authentication for a domain or email address. It lists specific outputs (MX, SPF, DMARC, free provider, disposable, verdict) and distinguishes from siblings like dns_lookup and domain_intel by focusing on email deliverability.

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 usage guidance: 'Use to qualify leads and flag throwaway signups.' It implies when to use this tool (lead qualification, signup validation). No explicit when-not-to-use or alternatives, but the single parameter and straightforward purpose make it sufficient.

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?

The description notes best-effort behavior, potential slowness, and a note on unavailability, which provides some behavioral context. Since no annotations exist, it carries the full burden but lacks explicit mention of read-only/non-destructive behavior or permission requirements.

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?

Three sentences capture the essential information without extraneous content. Every sentence adds value: what it does, when to use, and caveats.

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 a simple tool with one parameter and no output schema, the description covers the main purpose, use case, and limitations. It could briefly mention the typical output format (list of subdomains) but is adequate for a tool of this complexity.

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 covers 100% of parameters with a good description ('Registrable domain, e.g. stripe.com'). The description adds overall purpose but does not enhance parameter meaning 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 it discovers subdomains from Certificate Transparency logs (crt.sh), specifying the action, resource, and context. It distinguishes itself from sibling tools like dns_lookup or domain_intel by focusing specifically on subdomain enumeration via CT logs.

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 explains when to use it ('mapping a company's public surface') and includes a caveat about crt.sh speed and unavailability. However, it does not explicitly mention when not to use it or suggest alternative tools for related tasks.

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 the full burden of behavioral disclosure. It explains that the tool fetches the homepage, detects technologies, and returns page title, final URL, and response headers. It does not cover failure scenarios (e.g., non-resolving domain) but is otherwise transparent about core behavior.

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, front-loaded with the main purpose, and each sentence adds value. There is no redundancy or fluff. It is concise yet informative.

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 or nested objects), the description covers all necessary aspects: inputs, actions, outputs, and use cases. It is complete and leaves no critical 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 schema provides a clear description for the single parameter 'domain' ('Domain or full URL, e.g. shopify.com'), achieving 100% coverage. The tool description does not add further semantic detail about the parameter beyond what is in the schema, 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 purpose: 'Fingerprint the technology behind a website by fetching its homepage.' It lists specific technologies detected (web server, CMS, CDN, analytics) and outputs (page title, final URL, headers). This distinguishes it from sibling tools like dns_lookup and domain_intel, which have different focuses.

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 a use case ('Use for competitive research and lead enrichment'), which gives context for when to use the tool. However, it does not explicitly indicate when not to use it or compare it to alternatives like domain_intel or subdomains, which could help an agent decide.

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