domain-intel-mcp

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

With no annotations, the description bears full responsibility for behavioral disclosure. It states the external service (Cloudflare DNS-over-HTTPS) and lists all returned record types. While it doesn't cover errors, rate limits, or response structure, the simplicity of a read-only DNS lookup makes this adequate. A higher score would require explicit side-effect or error handling details.

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: two sentences, no fluff. Purpose appears first, followed by use cases. 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?

Given the tool's low complexity and full schema coverage, the description covers the essential behaviors: service provenance, record types, and use cases. It lacks explicit error/limitation notes (e.g., DNSSEC, timeouts) and doesn't differentiate from siblings, but these are minor gaps for a simple lookup 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?

Schema description coverage is 100%, so the schema already documents both parameters. The description restates the types parameter's optionality and example values, adding no new meaning beyond the schema. 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 action ('Look up DNS records'), the resource ('domain'), the method ('via Cloudflare DNS-over-HTTPS'), and the specific record types returned (A, AAAA, MX, NS, TXT, CNAME, SOA). It also provides concrete use cases (hosting location, mail/DNS operations, TXT records) which distinguishes it from sibling tools like domain_intel or tech_stack.

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 when to use the tool ('Use to see where a domain is hosted...'), giving clear context. However, it does not mention when not to use it or contrast with sibling tools; the absence of exclusions or alternatives is acceptable given the tool's straightforward nature.

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 bears full burden. It details the returned data and mentions the data source (RDAP), but does not disclose limitations such as behavior on nonexistent domains, rate limits, or data freshness.

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 with no redundant words. The first sentence defines the tool's purpose and outputs; the second lists use cases. Information is front-loaded and every sentence 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 tool with one required parameter, no output schema, and no annotations, the description covers the core functionality and typical use cases. It could be improved by briefly noting error handling (e.g., if RDAP lookup fails) or data source reliability, but the current level is sufficient.

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% (the 'domain' parameter is well described). The description provides an example ('e.g. stripe.com (no scheme)') which reinforces the schema but adds no additional semantic value beyond what the schema already conveys.

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 returns 'registration intelligence via RDAP' and lists specific data fields (registrar, dates, EPP codes, etc.). It distinguishes from sibling tools by focusing on registration data rather than DNS or technical stack, but does not explicitly name alternatives.

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 provides usage context ('vet a company, assess a lead, judge how established a domain is') but lacks explicit guidance on when not to use it or how it compares to siblings like 'domain_report' or 'dns_lookup'.

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 provided, so description carries full burden. It describes what the tool does but lacks details on error behavior, rate limits, or data freshness. Adequate but not fully transparent.

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, front-loaded sentence with no wasted 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?

Covers the four main areas of the combined report, but without an output schema, the description could elaborate on the report structure or returned fields.

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% and description only repeats the example (e.g., stripe.com) without adding constraints, formatting, or nuances 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?

Description clearly states it is a 'one-call full dossier' combining multiple data sources (RDAP, DNS, email, tech stack) and explicitly distinguishes from sibling tools like dns_lookup or subdomains.

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 tells when to use: 'for fast lead qualification, company research, or recon without four separate calls', implying alternatives are separate individual lookups.

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 provided, the description carries full burden. It discloses the checks performed (MX, SPF, DMARC, provider detection) and that it returns a verdict. However, it omits details like whether external queries are made, rate limits, or authentication requirements. Adequate but not thorough.

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 long, front-loading the purpose in the first sentence. Every sentence adds value: purpose, return values, and use case. No unnecessary 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?

Given the tool has a single parameter and no output schema, the description adequately explains what it returns and when to use it. It does not specify output format or error handling, but for a simple assessment tool it is reasonably 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?

The input schema already has 100% coverage describing the parameter 'domain_or_email' as 'A domain (stripe.com) or an email address (a@stripe.com)'. The description does not add new semantic meaning beyond the schema, so baseline score 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 tool assesses email deliverability and authentication for a domain or email, listing specific checks (MX, SPF, DMARC, free/disposable provider detection). This differentiates it from siblings like dns_lookup (general DNS) and domain_intel (WHOIS info).

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 advises using the tool to 'qualify leads and flag throwaway signups', providing clear context. It does not exclude alternative scenarios or compare directly with siblings, but the use case is well-defined.

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 disclose behavioral traits. It mentions best-effort, source (crt.sh), potential slowness, and a note on unavailability. However, it does not mention rate limits, return format, or whether it respects robots.txt. This is adequate but not exhaustive.

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, each essential. First sentence states core action and source, second gives use case, third sets expectations. No redundancy, 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?

For a simple tool with one parameter and no output schema, the description covers purpose, usage context, and limitations. It does not detail the return format (e.g., list of subdomains), but the mention of 'returns a note if unavailable' implies some structure. Overall, it is largely 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% with one well-described parameter. The description adds value by specifying 'registrable domain' and giving an example (stripe.com), helping the agent understand the expected input format 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 'Discover subdomains of a domain from public Certificate Transparency logs (crt.sh)', which is a specific verb+resource+source. It also gives a use case (mapping public surface) and examples, distinguishing it from sibling tools like dns_lookup or tech_stack.

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 says 'Useful for mapping a company's public surface', providing clear context on when to use. It also notes best-effort behavior and potential slowness. However, it does not explicitly state when not to use or compare to alternatives like dns_lookup.

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 exist, so the description must disclose behavioral traits. It explains the action (fetching homepage), what is detected (server, CMS, etc.), and what is returned (title, URL, headers). It does not mention potential issues like timeouts, restrictions on non-HTTP sites, or rate limits. However, the described behavior is accurate and sufficient for an agent to understand the tool's side effects.

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 with no extraneous words. The first sentence concisely states the action and deliverables; the second states use cases. Front-loaded with the core purpose. Every sentence 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?

Given the tool's simplicity (1 parameter, no output schema, no nested objects), the description covers the key returns: web server, CMS/framework, CDN, analytics, page title, final URL, headers. It does not detail failure handling or output format, but the information provided is sufficient for an agent to correctly invoke and interpret results.

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 single parameter 'domain' has 100% schema coverage with description 'Domain or full URL, e.g. shopify.com.' The tool description adds context by explaining what the tool does with the domain (fetches homepage). Since schema coverage is high, the description's added value is minimal but consistent, warranting a baseline score 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 the tool's purpose: 'Fingerprint the technology behind a website by fetching its homepage.' It lists specific detections (web server, CMS, CDN, analytics) and return elements (page title, final URL, headers). This distinguishes it from siblings like dns_lookup or domain_intel which analyze DNS or domain registration rather than web technology.

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 competitive research and lead enrichment.' It implies when to use (when technology detection is needed) but does not explicitly state when not to use or directly compare to siblings. Given sibling tools cover DNS, domain intel, etc., the context is clear, but a brief exclusion note would strengthen guidance.

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