Recruiter Fit-Claim Scorecard for SaaS Heads of Talent

A structured ledger that lets an in-house head of talent record the pre-interview 'fit claims' external search firms make about each candidate ('9/10 culture match', 'top of my pipeline', 'definitely worth a final round'), then grade those claims against eventual interview-panel scorecards, offer-acceptance, and 90-day retention pulled from the company's existing ATS. AE's adversarial debate stack scores claim language pre-interview for falsifiability vs. hedge-laden puffery; over weeks, per-firm calibration curves emerge — Firm A's 9/10s convert to offers 71% of the time; Firm B's convert 18%. The head of talent uses this to renegotiate retainers, drop low-calibration firms, and defend hiring-velocity numbers to the CEO with adjudicated evidence rather than vibes. AE is uniquely suited because the same grading-loop + lifecycle-state machinery that produced 508 graded predictions ports directly onto recruiter-claim resolution, and the manual-entry path means zero ATS integration is required for first paid engagement.

Recruiter fit-claims are unrecorded predictions with objective ATS-resolved outcomes — exactly AE's grading-loop shape, sold to a single introverted buyer with no integration friction.

Engine verdict: GATHER_MORE_SIGNAL (WORTH_SKIMMING). Real pain, open quadrant, but taxonomy port + buyer politics + async-solo distribution remain unverified — premature to build until weekend transferability test runs.