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due_diligence

Entity due diligence report. One call replaces 10+ separate lookups. Pass a domain or company name, get: WHOIS data, SSL certificate analysis, sanctions screening (OpenSanctions), web archive history, web presence audit, social links, contact info, risk signals, and a confidence-scored trust verdict (0-100). Costs $0.50 because it runs 5+ parallel checks and cross-references the results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainNoDomain to investigate (e.g., google.com)
companyNoCompany name to screen (e.g., Google LLC)

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the behavioral disclosure burden. It transparently states the cost ($0.50) and that it runs parallel checks, which is valuable. However, it does not clarify behavior when both domain and company are provided, error handling, or data freshness, leaving gaps in transparency for a tool with no annotation safety net.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with the core purpose and packs significant detail (list of outputs, cost justification) without being wordy. Each sentence adds value, though it could be slightly tighter by removing the redundant 'because it runs 5+ parallel checks' explanation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with no output schema, the description covers the return contents thoroughly, listing all data types and the confidence score range. It also explains the cost rationale. It lacks a mention of output format or duration, but given the exhaustive list, it is largely complete for an AI agent to understand what it will receive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already has 100% coverage with descriptions for both parameters. The description adds that you can pass 'a domain or company name,' implying they are alternatives, which is a slight clarification beyond the schema. But it doesn't elaborate on formats, precedence, or relationship between parameters, so it only meets the baseline for full schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Entity due diligence report' with a specific verb 'get' and a comprehensive list of data types (WHOIS, SSL, sanctions, etc.). It distinguishes itself from sibling tools by emphasizing it replaces 10+ separate lookups, making its scope unique compared to more targeted tools like domain_enrich or company_report.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'One call replaces 10+ separate lookups' gives clear usage context: use when you need multiple due diligence data points in one request. However, it does not explicitly mention when not to use it or name alternatives. It implies a comprehensive need but lacks explicit exclusions, so it misses a 5.

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

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TDQS

B3.4/5.0
Disambiguation2/5

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.

Naming Consistency4/5

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.

Tool Count3/5

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.

Completeness3/5

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.