didit-face-search

Name: didit-face-search
Availability: InStock
Author: Didit

Perform 1:N facial searches against verified sessions to detect duplicate registrations.

23|4|Updated Feb 14, 2026

Search Tags:#api #verification #deduplication #sessions #face-search #biometric

Ready to run

npx skills add https://github.com/didit-protocol/didit-agent-skills --skill didit-face-search

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: didit-face-search
Source: https://github.com/didit-protocol/didit-agent-skills/tree/main/skills/didit-face-search
Command: npx skills add https://github.com/didit-protocol/didit-agent-skills --skill didit-face-search

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Detect duplicates by performing 1:N facial searches against all previously verified sessions to identify potential duplicate registrations and blocklisted faces.

Core Features & Use Cases

1:N facial search against verified sessions to identify duplicates
Blocklist risk detection to prevent fraudulent accounts
Ranking & similarity scores to support automated decisioning in registration or identity workflows

Quick Start

Upload a user image and call the face-search API to retrieve matching sessions.

Frequently Asked Questions about didit-face-search

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I detect duplicate user registrations using facial search?▼

To detect duplicate user registrations, facial search performs a 1:N match against all previously verified sessions, returning ranked matches and similarity percentages to identify if the same face already exists in your identity workflows.

How does 1:N face search work for blocklist risk detection?▼

1:N face search works for blocklist risk detection by comparing a submitted user image against all previously verified sessions to flag blocklisted faces and prevent fraudulent account creations across identity workflows.

What do I need to perform a 1:N biometric face search via API?▼

To perform a 1:N biometric face search via API, you need a valid DIDIT_API_KEY and must send a POST request containing a user_image file to the /v3/face-search/ endpoint to retrieve matching sessions.

Can I use facial search ranking and similarity scores for automated decisioning?▼

Yes, you can use facial search ranking and similarity scores for automated decisioning in registration or identity workflows, as the API retrieves matching sessions with similarity percentages to support automated fraud prevention decisions.

Is there a way to prevent fraud by checking a user image against verified sessions?▼

You can prevent fraud by conducting a 1:N facial search that checks a new user image against all previously verified sessions, applying directly to registration deduplication and blocking blocklisted faces across identity workflows.

Why does face-search require a POST request with a user_image file?▼

Face-search requires a POST request with a user_image file because the API needs the raw biometric image data to perform the 1:N facial comparison against verified sessions and accurately calculate similarity percentages for duplicate detection.