Website security and SEO audit. Runs 5 parallel checks: security headers (HSTS, CSP, X-Frame-Options), SSL certificate grade, DNS configuration (DNSSEC, SPF), SEO analysis (title, meta, OG tags, headings, images), and Lighthouse performance metrics. Returns scored report (0-100) with actionable findings. $0.50 per audit.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit (e.g., https://example.com) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that it runs parallel checks, returns a scored report with actionable findings, and mentions the cost ($0.50), which is useful behavioral context. Could add more about failure modes or timeouts, but it's a solid 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 a single paragraph, but it's information-dense and well-structured, listing checks clearly. It's slightly long but every sentence adds value. Adding line breaks could improve readability, but it's still concise.
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 (multiple checks) and the simple, fully covered schema, the description provides complete context: what it does, what it returns, and even pricing. No output schema exists, but the description covers the return format. It's comprehensive enough.
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 describes the URL parameter with an example, so coverage is 100%. The description doesn't add much parameter semantics beyond that, but it's redundant given the schema. Baseline 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 uses a specific verb ('Runs') and a clear resource ('Website security and SEO audit'), and explicitly lists the five distinct checks performed. This clearly distinguishes it from sibling tools like 'email_audit' and 'web_scrape'.
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 when to use it: for comprehensive security and SEO audits. It doesn't explicitly state when not to use it or compare with alternatives, but the detailed scope makes the use case evident. Slight deduction for lacking explicit exclusions.
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.