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theharvester_search

Gather OSINT data by searching a domain for emails, subdomains, IPs, and URLs using multiple public sources. Specify target domain and optional sources to collect open-source intelligence for penetration testing.

Instructions

OSINT gathering using theHarvester (emails, subdomains, IPs, URLs). domain: target domain or company name source: comma-separated data sources. Defaults to sources that work without API keys. Full list: google, bing, linkedin, github, dnsdumpster, crtsh, hackertarget, otx, rapiddns, shodan (needs key), sublist3r, threatminer, urlscan, duckduckgo Use 'all' only if you have API keys configured. limit: max search results (default 500) dns_resolve: perform DNS resolution on discovered subdomains

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
domainYes
sourceNocrtsh,duckduckgo,hackertarget,otx,rapiddns,urlscan,commoncrawl
dns_resolveNo
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It mentions API key requirements for some sources and explains default behavior for DNS resolution, but it does not disclose potential rate limits, external network requests, or output format beyond the listed data types. It adds moderate value but lacks deeper behavioral context.

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

Conciseness5/5

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

The description is compact and well-structured with line breaks per parameter. Each sentence adds value: purpose, source options, API key caveat, and parameter meanings. No filler or redundancy.

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 4-parameter tool with no output schema, the description covers all input semantics and necessary usage caveats. It lacks an explicit description of the return value structure, but that's not required for invocation. Given the moderate complexity, it is nearly complete for the agent to select and call the tool correctly.

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

Parameters5/5

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

The schema has zero description coverage, so the tool description fully compensates. It explains domain as 'target domain or company name', source as 'comma-separated data sources' with a full list and default, limit as 'max search results' with default, and dns_resolve as 'perform DNS resolution on discovered subdomains'. Every parameter is meaningfully described.

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

Purpose4/5

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

The description states 'OSINT gathering using theHarvester (emails, subdomains, IPs, URLs)' with a specific verb and resource. It lists the data types collected, which helps distinguish it from subdomain-only tools like subfinder_enumerate or amass_enum, though it doesn't 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.

Usage Guidelines3/5

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

The description gives clear guidance on source selection ('Defaults to sources that work without API keys', 'Use all only if you have API keys configured') but does not explicitly state when to choose this tool over sibling tools like subfinder or amass. Usage context is implied rather than explicitly contrasted.

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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