Who This Is For
- Recruitment teams
- HR operations
- Teams managing resume and internal knowledge
Typical Needs
- Repetitive resume整理
- Scattered interview and job data
- Inconsistent internal knowledge and process docs
Suitable vs Not Suitable
Suitable for AI assist
- Resume field extraction
- JD vs candidate matching
- Interview prep and materials
- Internal FAQ and process助手
Not suitable for full AI handoff
- Unexplainable reject conclusions
- Contacting candidates without human approval
- Bulk access to candidate data without controls
- Using scores as final hire/no-hire decision
Minimum Viable Delivery
- Read resumes or JD docs
- Output structured extraction
- Human review before any action
Human Review Required
HR workflows must keep humans in the loop:
- AI assists with structuring, matching, and prep
- Final judgment and external actions stay with people
- All conclusions traceable to source material
Bias and Privacy
- Don’t base decisions on protected attributes
- Limit data scope and access
- Run security audit before production:
openclaw security audit --deep
Success Criteria
- Less prep time
- More consistent structures
- Easier sharing of interview materials
Next Steps
-
Resume screening pipeline — fields, JD match, review flow
-
Internal knowledge base — onboarding FAQ and process docs
-
Official docs → docs.openclaw.ai
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Issues → GitHub Issues