dataforseo-domain-analytics-api_skill

This skill helps enrich and analyze domains using DataForSEO Domain Analytics to detect tech stacks, research domains, and enhance lead data.

0

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill leonardo-picciani/dataforseo-agent-skills --skill dataforseo-domain-analytics-api

  • SKILL.md4.9 KB

Overview

This skill integrates DataForSEO Domain Analytics to enrich and analyze domains for technology detection, domain research, and lead enrichment. It surfaces CMS, frameworks, analytics, hosting, and WHOIS signals to support prospecting, competitive analysis, and risk scoring. Use it for live lookups or task-based batch processing depending on volume and latency needs.

How this skill works

The skill calls DataForSEO Domain Analytics endpoints using HTTP Basic auth and either live (single-request) or task-based flows. For live endpoints it returns immediate technology and WHOIS summaries; for task flows it posts tasks, polls tasks_ready, then fetches task_get results or consumes pingback notifications. Responses are validated by status_code and tasks[].status; the skill normalizes summaries and preserves raw payloads for debugging.

When to use it

  • Detect the tech stack of a single site or small list interactively (live endpoints).
  • Enrich large lead lists with CMS, analytics, hosting, and WHOIS data (task-based).
  • Build targeted prospect lists by technology, location, or language filters.
  • Monitor competitor or customer stack changes and replatforming events.
  • Add WHOIS and domain registration signals into fraud, risk, or compliance scoring.

Best practices

  • Choose live mode for low-latency, single-domain queries and task mode for bulk or scheduled jobs.
  • Always validate top-level status_code == 20000 and check each tasks[].status before trusting data.
  • Store tasks[].id and use tasks_ready + task_get or webhook postback for reliable retrieval in task flows.
  • Include location and language filters when regional accuracy matters (technologies locations/languages endpoints).
  • Return both a concise normalized summary and the raw response payload to aid debugging and audits.

Example use cases

  • Find US domains running Shopify and produce a ranked prospect list with contact enrichment.
  • Run a WHOIS overview for a batch of domains to flag risky registration patterns and registrar anomalies.
  • Enrich an inbound lead list with CMS, analytics, and hosting signals for SDR prioritization.
  • Compare technology footprints between our domain and competitors and summarize differences by category.

FAQ

You need DataForSEO login and password used for HTTP Basic auth (Authorization: Basic base64(login:password)).

When should I use live vs task endpoints?

Use live endpoints for immediate, single or small-number lookups. Use task-based endpoints for high-volume, scheduled, or long-running operations where polling or webhooks are preferable.

How do I know a response is valid?

Treat any status_code != 20000 as a failure and surface status_message. For tasks, also verify each tasks[].status and only fetch results when tasks_ready indicates completion.

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