DataForSEO

Search Google and gather SEO data using the DataForSEO API. Supports SERP results, keyword data, backlinks, and on-page analysis. Use when you need high-volu...

Security Scan

The skill's behavior (calling DataForSEO endpoints with BASIC-auth credentials) matches its stated purpose, but there is a notable metadata mismatch and provenance unknown — exercise caution before providing credentials.

Purpose & Capability

The SKILL.md implements DataForSEO API calls and requires DATAFORSEO_LOGIN and DATAFORSEO_PASSWORD, which are coherent with the described purpose (SERP, keywords, backlinks). However the registry metadata provided with the skill (outside of SKILL.md) lists no required environment variables or homepage/source — that mismatch is unexpected and reduces provenance/trust.

Instruction Scope

The instructions are narrowly scoped to calling DataForSEO endpoints (posting tasks, polling results, maps, keyword endpoints). They do not instruct reading unrelated files, system paths, or contacting third-party endpoints beyond the DataForSEO API domains shown. The SKILL.md explicitly requires env vars and shows code that uses only those env vars.

Install Mechanism

This is an instruction-only skill with no install spec and no code files to be written to disk, which is the lowest-risk install model.

Credentials

The SKILL.md requests a login and password (DATAFORSEO_LOGIN, DATAFORSEO_PASSWORD) which is proportionate to calling the DataForSEO API. The concern is twofold: (1) the skill registry metadata supplied with the skill claims no required env vars, yet the runtime instructions clearly require credentials — a mismatch that could hide the fact the skill will access secrets; (2) it uses basic auth with an email/password rather than a scoped API key or token, meaning supplied credentials may grant broad access to the upstream account (billing, deposit).

Persistence & Privilege

The skill does not request always:true, does not modify other skills or system settings, and has no install steps that persist code. It runs only when invoked and has normal autonomous-invocation defaults.

What to consider before installing

This skill appears to do what it says (calls DataForSEO endpoints) but the package metadata is inconsistent and the source/homepage is missing. Before installing or supplying credentials: 1) Verify the skill publisher (the owner ID is opaque) and prefer skills with a verifiable homepage or source repo. 2) Confirm DataForSEO actually requires email/password for API access — if possible use a scoped API key or token instead of your primary account password. 3) If you must provide credentials, create a dedicated DataForSEO account with minimal funds/deposit to limit blast radius and avoid using your primary billing account. 4) Ask the publisher or registry to correct the manifest so required env vars are declared properly (the current SKILL.md requires env vars but the registry metadata lists none). 5) Monitor logs and network activity; do not share credentials with untrusted skills. If you need higher assurance, request a source repository or signed release before use.

DataForSEO Skill

Pay-as-you-go Google SERP + SEO data API. Best for high-volume lead generation at low cost. No monthly commitment — only pay for what you use.

Credentials

DATAFORSEO_LOGIN=[e-mail]
DATAFORSEO_PASSWORD=your_password

Sign up at dataforseo.com. Minimum deposit: $50. Cost per SERP task: ~$0.0006 (very cheap for bulk).

Quick Usage — SERP Search

import requests, os, json
from base64 import b64encode

def dfs_auth():
    creds = f"{os.environ['DATAFORSEO_LOGIN']}:{os.environ['DATAFORSEO_PASSWORD']}"
    return b64encode(creds.encode()).decode()

def dfs_search(keyword: str, location: str = "United States", language: str = "en") -> list[dict]:
    """
    Search Google via DataForSEO Live SERP endpoint.
    Returns organic results: {url, title, description, rank_absolute, domain}
    """
    headers = {
        "Authorization": f"Basic {dfs_auth()}",
        "Content-Type": "application/json"
    }
    payload = [{
        "keyword": keyword,
        "location_name": location,
        "language_name": language,
        "device": "desktop",
        "os": "windows",
        "depth": 10
    }]
    
    url = "https://api.dataforseo.com/v3/serp/google/organic/live/advanced"
    r = requests.post(url, headers=headers, json=payload)
    r.raise_for_status()
    
    data = r.json()
    tasks = data.get("tasks", [])
    if not tasks or tasks[0]["status_code"] != 20000:
        return []
    
    items = tasks[0]["result"][0].get("items", [])
    organic = [i for i in items if i.get("type") == "organic"]
    
    return [{
        "title": i.get("title"),
        "url": i.get("url"),
        "description": i.get("description"),
        "rank": i.get("rank_absolute"),
        "domain": i.get("domain")
    } for i in organic]

Lead Generation — Batch Mode (Most Efficient)

def dfs_batch_search(queries: list[str], location: str = "United States") -> dict[str, list]:
    """
    Submit multiple queries in one API call (up to 100).
    Much more efficient — one round trip for many queries.
    Returns dict: {query: [results]}
    """
    headers = {
        "Authorization": f"Basic {dfs_auth()}",
        "Content-Type": "application/json"
    }
    
    # Build task list
    tasks = [{
        "keyword": q,
        "location_name": location,
        "language_name": "en",
        "device": "desktop",
        "depth": 10,
        "tag": q  # use query as tag for matching results
    } for q in queries]
    
    # Submit tasks
    url = "https://api.dataforseo.com/v3/serp/google/organic/task_post"
    r = requests.post(url, headers=headers, json=tasks)
    task_ids = [t["id"] for t in r.json()["tasks"] if t["status_code"] == 20100]
    
    # Poll for results (tasks complete in ~10–60 seconds)
    import time
    time.sleep(15)
    
    results = {}
    for task_id in task_ids:
        result_url = f"https://api.dataforseo.com/v3/serp/google/organic/task_get/advanced/{task_id}"
        res = requests.get(result_url, headers=headers)
        items = res.json()["tasks"][0]["result"][0].get("items", [])
        organic = [i for i in items if i.get("type") == "organic"]
        tag = res.json()["tasks"][0].get("tag", task_id)
        results[tag] = [{"title": i["title"], "url": i["url"], "domain": i.get("domain")} for i in organic]
    
    return results

Available API Endpoints

Category	Endpoint	Use Case
SERP (live)	/serp/google/organic/live/advanced	Single query, instant result
SERP (async)	/serp/google/organic/task_post	Bulk queries, cheaper
SERP (local)	/serp/google/organic/live/advanced + location_code	City-specific results
Maps	/serp/google/maps/live/advanced	Local business + phone + website
Keywords	/keywords_data/google_ads/search_volume/live	Search volume data
On-Page	/on_page/task_post	Full site audit
Backlinks	/backlinks/summary/live	Link profile

Maps Search (Best for Local Lead Gen)

def dfs_maps_search(query: str, location_code: int = 1023191) -> list[dict]:
    """
    Search Google Maps for local businesses.
    Returns: {title, url, phone, address, rating, reviews_count}
    location_code 1023191 = Portland, OR. Find codes at:
    https://api.dataforseo.com/v3/serp/google/locations
    """
    headers = {"Authorization": f"Basic {dfs_auth()}", "Content-Type": "application/json"}
    payload = [{
        "keyword": query,
        "location_code": location_code,
        "language_code": "en",
        "device": "desktop"
    }]
    url = "https://api.dataforseo.com/v3/serp/google/maps/live/advanced"
    r = requests.post(url, headers=headers, json=payload)
    items = r.json()["tasks"][0]["result"][0].get("items", [])
    return [{
        "title": i.get("title"),
        "url": i.get("url"),
        "phone": i.get("phone"),
        "address": i.get("address"),
        "rating": i.get("rating", {}).get("value"),
        "reviews": i.get("rating", {}).get("votes_count"),
        "category": i.get("category")
    } for i in items if i.get("type") == "maps_search"]

Location Codes (Common US Cities)

LOCATION_CODES = {
    "Portland, OR": 1023191,
    "Seattle, WA": 1027744,
    "Dallas, TX": 1026339,
    "Chicago, IL": 1016367,
    "Los Angeles, CA": 1013962,
    "New York, NY": 1023191,
    "Denver, CO": 1016143,
    "Phoenix, AZ": 1023725,
    "Atlanta, GA": 1013971,
    "Miami, FL": 1017862,
}
# Full list: GET https://api.dataforseo.com/v3/serp/google/locations

Pricing Reference

Task Type	Cost Per 1K
SERP Live	~$1.50
SERP Async (batch)	~$0.60
Maps Live	~$2.00
Keywords (search vol)	~$0.50

For lead gen at 50 queries/day: ~$0.03–$0.08/day.

When to Use DataForSEO vs Serper

Scenario	Use
Quick test / low volume	Serper.dev (free tier)
High volume (500+ queries/day)	DataForSEO (cheaper at scale)
Need Google Maps data (phone+website)	DataForSEO Maps endpoint
Need keyword volume data	DataForSEO Keywords
Need backlink data	DataForSEO Backlinks
Just need organic results fast	Serper.dev