Tool Landing
JD Parser
Convert raw job text into structured JSON-style requirement blocks in seconds.
What comes out
- Extract requirements, responsibilities, and skill signals from messy JD text
- Surface interview focus areas before you rewrite your resume
- Use parsed output as input for report generation and ATS matching
Preview output
Structured extraction preview
Role: SOC Analyst (Hong Kong)
Core requirements: SIEM triage, incident escalation, detection tuning
Tool keywords: KQL, Sigma
Example input
Jd
We are hiring a SOC Analyst in Hong Kong. You will own SIEM triage, incident escalation, and detection tuning with KQL/Sigma.
Example output
Headline
Structured extraction preview
Points
Role: SOC Analyst (Hong Kong), Core requirements: SIEM triage, incident escalation, detection tuning, Tool keywords: KQL, Sigma
FAQ
Does JD parsing consume credits?
JD parsing itself is zero-credit. Quotas apply when you save a new JD into your library.
How accurate is extraction for long JDs?
Accuracy improves when the JD includes concrete requirements and responsibilities. You can always edit before saving.
Can I use this for non-English JDs?
Yes. OpenView supports multilingual text parsing and role signal extraction.