dataforseo-backlinks-api
3
总安装量
3
周安装量
#57994
全站排名
安装命令
npx skills add https://github.com/manojbajaj95/gtm-skills --skill dataforseo-backlinks-api
Agent 安装分布
gemini-cli
3
claude-code
3
codex
3
opencode
3
qoder
2
replit
2
Skill 文档
DataForSEO Backlinks API
Provenance
This is an experimental project to test how OpenCode, plugged into frontier LLMs (OpenAI GPT-5.2), can help generate high-fidelity agent skill files for API integrations.
When to Apply
- “get backlinks for domain/url”, “referring domains”, “anchors report”
- “monitor new and lost backlinks”, “link velocity”, “timeseries backlinks”
- “bulk backlink checks”, “bulk ranks”, “spam score checks”
- “competitor backlink research”, “link gap analysis”
Integration Contract (Language-Agnostic)
See references/REFERENCE.md for the shared DataForSEO integration contract (auth, status handling, task lifecycle, sandbox, and .ai responses).
Live-first Endpoints
- Backlinks endpoints are typically Live-first and support pagination-like controls (e.g., result limits) and filtering/sorting.
- The Index endpoint provides up-to-the-moment information about the backlinks database.
Steps
- Identify the exact endpoint(s) in the official docs for this use case.
- Choose execution mode:
- Live (single request) for interactive queries
- Task-based (post + poll/webhook) for scheduled or high-volume jobs
- Build the HTTP request:
- Base URL:
https://api.dataforseo.com/ - Auth: HTTP Basic (
Authorization: Basic base64(login:password)) from https://docs.dataforseo.com/v3/auth/ - JSON body exactly as specified in the endpoint docs
- Base URL:
- Execute and validate the response:
- Check top-level
status_codeand eachtasks[]item status - Treat any
status_code != 20000as a failure; surfacestatus_message
- Check top-level
- For task-based endpoints:
- Store
tasks[].id - Poll
tasks_readythen fetch results withtask_get(or usepostback_url/pingback_urlif supported)
- Store
- Return results:
- Provide a normalized summary for the user
- Include the raw response payload for debugging
Inputs Checklist
- Credentials: DataForSEO API login + password (HTTP Basic Auth)
- Target: keyword(s) / domain(s) / URL(s) / query string (depends on endpoint)
- Targeting (if applicable): location + language, device, depth/limit
- Time window (if applicable): date range, trend period, historical flags
- Output preference: regular vs advanced vs html (if the endpoint supports it)
Example (cURL)
curl -u "${DATAFORSEO_LOGIN}:${DATAFORSEO_PASSWORD}" -H "Content-Type: application/json" -X POST "https://api.dataforseo.com/v3/<group>/<path>/live" -d '[
{
"<param>": "<value>"
}
]'
Notes:
- Replace
<group>/<path>with the exact endpoint path from the official docs. - For task-based flows, use the corresponding
task_post,tasks_ready, andtask_getendpoints.
Docs Map (Official)
- Overview: https://docs.dataforseo.com/v3/backlinks/overview/
- Index: https://docs.dataforseo.com/v3/backlinks/index/
Core endpoints:
- Summary (Live): https://docs.dataforseo.com/v3/backlinks/summary/live/
- Backlinks (Live): https://docs.dataforseo.com/v3/backlinks/backlinks/live/
- Referring Domains (Live): https://docs.dataforseo.com/v3/backlinks/referring_domains/live/
Business & Product Use Cases
- Link monitoring: alerts for new/lost backlinks and anchor shifts.
- Link building: find competitor links and prioritize outreach targets.
- Risk management: detect suspicious patterns and possible negative SEO.
- Agency reporting: monthly link growth and top referring domains.
- M&A diligence: evaluate a domain’s authority/link profile before acquisition.
- Publisher partnerships: identify strong referring networks for co-marketing.
Examples (User Prompts)
- “If you don’t have the skill installed, install
dataforseo-backlinks-apiand then continue.” - “Install the Backlinks skill and audit our backlink profile: top ref domains, anchors, and spam risks.”
- “Track new and lost backlinks weekly and alert me to big drops.”
- “Find competitor backlinks we don’t have and suggest outreach targets.”
- “Run a bulk check of these 200 domains: ranks + referring domains count.”
- “Analyze anchor distribution and flag over-optimized patterns.”