Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Updated API refs, added utility script and feature guide
What This Skill Does
Performs 1:N facial search by comparing a submitted photo against all previously approved verification sessions in a Didit application. Returns ranked matches with similarity scores from 0-100. Blocklist matches trigger automatic decline.
Unlike 1:1 face comparison, it searches the entire approved session database in one call, so no prior session ID is needed to detect duplicates or blocklist hits.
When to use it
- Blocking duplicate account registrations during onboarding
- Checking a new user's face against a fraud blocklist
- Flagging users who attempt to re-register under a different identity
- Reviewing borderline similarity matches for manual investigation
- Running facial deduplication as part of a multi-step verification pipeline
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Check if this selfie already exists in our verified user database
- 1Validates the image meets format and size requirements (JPEG/PNG/WebP/TIFF, max 5MB)
- 2POSTs the image to https://verification.didit.me/v3/face-search/ with the DIDIT_API_KEY header
- 3Parses the response status: Approved (no matches), In Review (possible duplicates), or Declined (blocklist hit)
- 4Extracts similarity_percentage and vendor_data from each match to identify overlapping accounts
- 5Flags matches above 90% as likely duplicates and those in the 70-89% range for manual review
List of matching sessions with similarity scores, partial user details, and a recommendation on whether to allow or block the registration
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.