Domain infrastructure map. Full DNS records (A, AAAA, MX, NS, TXT, SOA, CAA), hosting provider, CDN detection, subdomain discovery via DNS brute-force and Certificate Transparency, IP geolocation.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain to map (e.g., google.com) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description bears full responsibility. It mentions specific actions (DNS brute-force, Certificate Transparency subdomain discovery, IP geolocation) which imply network calls, but it does not disclose potential rate limits, response format, or that it is strictly read-only. It lacks explicit behavioral guarantees beyond listing its scope.
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 concise sentence that front-loads the core purpose ('Domain infrastructure map') followed by a dense, comma-separated list of features. No wasted words, every element 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 complexity (various DNS records, subdomain discovery, geolocation) and lack of output schema, the description provides a thorough enumeration of what is returned. It does not mention prerequisites or limitations, but it covers the main behavioral aspects adequately for an initial invocation.
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 only parameter 'domain' is well-described in the schema with an example. The description does not add any additional syntax, constraints, or format details beyond what the schema provides. With 100% schema coverage, the baseline 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: 'Domain infrastructure map' with a comprehensive list of DNS record types and additional features like hosting provider, CDN detection, subdomain discovery, and IP geolocation. It distinguishes from siblings like 'domain_enrich' by specifying the full scope of DNS records and subdomain discovery techniques.
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 comprehensive domain infrastructure mapping but does not explicitly compare to alternatives (e.g., 'domain_enrich') or state when not to use it. The agent can infer the tool's broad scope, but there is no explicit guidance on when to choose this over similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools have overlapping functionality, such as domain_infra, company_report, and due_diligence all covering DNS/WHOIS/SSL checks. Similarly, web_scrape and scrape_structured both extract website content, and verify_email overlaps with email_audit on DNS-based email checks. This creates ambiguity in tool selection, especially for agents looking for a specific type of analysis.
All tool names use lowercase with underscores, which provides a consistent style. However, the grammatical pattern varies: some are verb-object (verify_email, currency_convert), some are noun-noun (domain_infra, site_audit), and others are adjective-noun (arabic_sentiment, brand_scout). This is not chaotic, but it lacks a rigid verb_noun convention, making it slightly less predictable.
With 25 tools, this sits at the upper boundary of what is considered 'heavy' but is still usable. The server covers a wide range of domains (Arabic NLP, web scraping, domain/email analysis, finance, faith), so the count is justified to a degree, but agents may be overwhelmed by choice. It is borderline appropriate for such a broad utility server.
The tool surface covers many common operations (scraping, DNS checks, email verification, financial data), but there are notable gaps. For example, no generic translation tool exists, only Arabizi-to-Arabic, and there is no text generation or embedding. While the set is extensive, it is not fully comprehensive for the diverse domains it touches, leaving some obvious missing operations.