Evaluation Engine.
Efficient evaluation of Web3 talent requires a shift from credentials to contributions. Use high-density signals to identify elite output with cryptographic certainty.
Prioritize attested history.
Focus on records verified by founders, organizations, or collaborators. These represent social capital anchored in real output and institutional trust.
Example Signal
Attestation from Superteam: "Role, Lead Smart Contract Developer."
Evaluate work, not titles.
Web3 roles are fluid. Look for high-frequency contributions and consistency across multiple milestones to identify substance over narrative claims.
Example Signal
Timeline Activity: 12 months, 4 projects, 15 verifiable proofs.
Signal Interpretation Framework
Use this structured framework to map candidate data points directly to your hiring decision metrics within the recruiter interface.
Authority Signal (Trust Layer)
Prioritize attested history. Focus on records verified by founders, organizations, or collaborators.
Map to Dashboard:
- Authority rate
- Institutional trust
Signal Density (Consistency)
Evaluate consistency of output. Look for multiple proofs and continuous activity over time.
Map to Dashboard:
- Signal density
- Proof count
- Timeline activity
Portfolio Authority (Depth)
Assess quality and credibility of work. Distinguish between attested and non-attested outputs.
Map to Dashboard:
- Portfolio authority
Strategic Fit (Context Match)
Match candidate signals with role requirements and contribution relevance.
Map to Dashboard:
- Strategic fit
Confidence Score (Decision Layer)
Use combined signals to determine hiring confidence (High / Medium / Low).
Map to Dashboard:
- Signal confidence indicator
Evaluate talent with dashboard metrics.
Access deep signal metrics for every applicant in your pipeline.