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Integrate Didit Face Search standalone API to perform 1:N facial search against all previously verified sessions. Use when the user wants to detect duplicate accounts, search for matching faces, check if a face already exists in the system, prevent duplicate registrations, search
Integrate Didit Face Search standalone API to perform 1:N facial search against all previously verified sessions. Use when the user wants to detect duplicate accounts, search for matching faces, check if a face already exists in the system, prevent duplicate registrations, search against blocklist, or implement facial deduplication using Didit. Returns ranked matches with similarity percentages.
Source documentation, not instructions for this website. Review permissions before running any commands.
Compares a reference face against all previously approved verification sessions to detect duplicate accounts and blocklisted faces. Returns ranked matches with similarity scores.
Key constraints:
Similarity score guidance:
| Range | Interpretation |
|---|---|
| 90%+ | Strong likelihood of same person |
| 70-89% | Possible match, may need manual review |
| Below 70% | Likely different individuals |
API Reference: https://docs.didit.me/standalone-apis/face-search Feature Guide: https://docs.didit.me/core-technology/face-search/overview
All requests require x-api-key header. Get your key from Didit Business Console → API & Webhooks, or via programmatic registration (see below).
If you don't have a Didit API key, create one in 2 API calls:
POST https://apx.didit.me/auth/v2/programmatic/register/ with {"email": "you@gmail.com", "password": "MyStr0ng!Pass"}POST https://apx.didit.me/auth/v2/programmatic/verify-email/ with {"email": "you@gmail.com", "code": "A3K9F2"} → response includes api_keyTo add credits: GET /v3/billing/balance/ to check, POST /v3/billing/top-up/ with {"amount_in_dollars": 50} for a Stripe checkout link.
See the didit-verification-management skill for full platform management (workflows, sessions, users, billing).
POST https://verification.didit.me/v3/face-search/
| Header | Value | Required |
|---|---|---|
x-api-key | Your API key | Yes |
Content-Type | multipart/form-data | Yes |
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
user_image | file | Yes | — | Face image to search (JPEG/PNG/WebP/TIFF, max 5MB) |
rotate_image | boolean | No | false | Try 0/90/180/270 rotations for non-upright faces |
save_api_request | boolean | No | true | Save in Business Console |
vendor_data | string | No | — | Your identifier for session tracking |
import requests
response = requests.post(
"https://verification.didit.me/v3/face-search/",
headers={"x-api-key": "YOUR_API_KEY"},
files={"user_image": ("photo.jpg", open("photo.jpg", "rb"), "image/jpeg")},
)
print(response.json())
const formData = new FormData();
formData.append("user_image", photoFile);
const response = await fetch("https://verification.didit.me/v3/face-search/", {
method: "POST",
headers: { "x-api-key": "YOUR_API_KEY" },
body: formData,
});
{
"request_id": "a1b2c3d4-...",
"face_search": {
"status": "Approved",
"total_matches": 1,
"matches": [
{
"session_id": "uuid-...",
"session_number": 1234,
"similarity_percentage": 95.2,
"vendor_data": "user-456",
"verification_date": "2025-06-10T10:30:00Z",
"user_details": {
"name": "Elena Martinez",
"document_type": "Identity Card",
"document_number": "***456"
},
"match_image_url": "https://example.com/match.jpg",
"status": "Approved",
"is_blocklisted": false
}
],
"user_image": {
"entities": [
{"age": "27.6", "bbox": [40, 40, 120, 120], "confidence": 0.95, "gender": "female"}
],
"best_angle": 0
},
"warnings": []
}
}
| Status | Meaning | Action |
|---|---|---|
"Approved" | No concerning matches found | Proceed — new unique user |
"In Review" | Matches above similarity threshold | Review matches[] for potential duplicates |
"Declined" | Blocklist match or policy violation | Check matches[].is_blocklisted and warnings |
| Code | Meaning | Action |
|---|---|---|
400 | Invalid request | Check file format, size, parameters |
401 | Invalid API key | Verify x-api-key header |
403 | Insufficient credits | Top up at business.didit.me |
| Field | Type | Description |
|---|---|---|
session_id | string | UUID of the matching session |
session_number | integer | Session number |
similarity_percentage | float | 0-100 similarity score |
vendor_data | string | Your reference from the matching session |
verification_date | string | ISO 8601 timestamp |
user_details.name | string | Name from the matching session |
user_details.document_type | string | Document type used |
user_details.document_number | string | Partially masked document number |
match_image_url | string | Temporary URL (expires 4 hours) |
status | string | Status of the matching session |
is_blocklisted | boolean | Whether the match is from the blocklist |
| Field | Type | Description |
|---|---|---|
entities[].age | string | Estimated age |
entities[].bbox | array | Face bounding box [x1, y1, x2, y2] |
entities[].confidence | float | Detection confidence (0-1) |
entities[].gender | string | "male" or "female" |
best_angle | integer | Rotation applied (0, 90, 180, 270) |
| Tag | Description |
|---|---|
NO_FACE_DETECTED | No face found in image |
FACE_IN_BLOCKLIST | Face matches a blocklisted entry |
| Tag | Description |
|---|---|
MULTIPLE_FACES_DETECTED | Multiple faces detected — unclear which to use |
Similarity threshold and allow multiple faces settings are configurable in Console.
Warning severity: error (→ Declined), warning (→ In Review), information (no effect).
1. During new user registration
2. POST /v3/face-search/ → {"user_image": selfie}
3. If total_matches == 0 → new unique user
If matches found → check similarity_percentage:
90%+ → likely duplicate, investigate matches[].vendor_data
70-89% → possible match, flag for manual review
1. POST /v3/passive-liveness/ → verify user is real
2. POST /v3/face-search/ → check for existing accounts
3. POST /v3/id-verification/ → verify identity document
4. POST /v3/face-match/ → compare selfie to document photo
5. All Approved → verified, unique, real user
Security: Match image URLs expire after 4 hours. Store only
session_idandsimilarity_percentage— minimize biometric data on your servers.
search_faces.py: Search for matching faces from the command line.
# Requires: pip install requests
export DIDIT_API_KEY="your_api_key"
python scripts/search_faces.py selfie.jpg
python scripts/search_faces.py photo.png --rotate --vendor-data user-123
name: didit-face-search
description: >
Integrate Didit Face Search standalone API to perform 1:N facial search against all
previously verified sessions. Use when the user wants to detect duplicate accounts,
search for matching faces, check if a face already exists in the system, prevent
duplicate registrations, search against blocklist, or implement facial deduplication
using Didit. Returns ranked matches with similarity percentages.
version: 1.2.0
metadata:
openclaw:
requires:
env:
- DIDIT_API_KEY
primaryEnv: DIDIT_API_KEY
emoji: "🔍"
homepage: https://docs.didit.me---
name: didit-face-search
description: >
Integrate Didit Face Search standalone API to perform 1:N facial search against all
previously verified sessions. Use when the user wants to detect duplicate accounts,
search for matching faces, check if a face already exists in the system, prevent
duplicate registrations, search against blocklist, or implement facial deduplication
using Didit. Returns ranked matches with similarity percentages.
version: 1.2.0
metadata:
openclaw:
requires:
env:
- DIDIT_API_KEY
primaryEnv: DIDIT_API_KEY
emoji: "🔍"
homepage: https://docs.didit.me
---
# Didit Face Search API (1:N)
## Overview
Compares a reference face against **all previously approved verification sessions** to detect duplicate accounts and blocklisted faces. Returns ranked matches with similarity scores.
**Key constraints:**
- Supported formats: **JPEG, PNG, WebP, TIFF**
- Maximum file size: **5MB**
- Compares against all **approved** sessions in your application
- Blocklist matches cause **automatic decline**
**Similarity score guidance:**
| Range | Interpretation |
|---|---|
| 90%+ | Strong likelihood of same person |
| 70-89% | Possible match, may need manual review |
| Below 70% | Likely different individuals |
**API Reference:** https://docs.didit.me/standalone-apis/face-search
**Feature Guide:** https://docs.didit.me/core-technology/face-search/overview
---
## Authentication
All requests require `x-api-key` header. Get your key from [Didit Business Console](https://business.didit.me) → API & Webhooks, or via programmatic registration (see below).
## Getting Started (No Account Yet?)
If you don't have a Didit API key, create one in 2 API calls:
1. **Register:** `POST https://apx.didit.me/auth/v2/programmatic/register/` with `{"email": "you@gmail.com", "password": "MyStr0ng!Pass"}`
2. **Check email** for a 6-character OTP code
3. **Verify:** `POST https://apx.didit.me/auth/v2/programmatic/verify-email/` with `{"email": "you@gmail.com", "code": "A3K9F2"}` → response includes `api_key`
**To add credits:** `GET /v3/billing/balance/` to check, `POST /v3/billing/top-up/` with `{"amount_in_dollars": 50}` for a Stripe checkout link.
See the **didit-verification-management** skill for full platform management (workflows, sessions, users, billing).
---
## Endpoint
```
POST https://verification.didit.me/v3/face-search/
```
### Headers
| Header | Value | Required |
|---|---|---|
| `x-api-key` | Your API key | **Yes** |
| `Content-Type` | `multipart/form-data` | **Yes** |
### Request Parameters (multipart/form-data)
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| `user_image` | file | **Yes** | — | Face image to search (JPEG/PNG/WebP/TIFF, max 5MB) |
| `rotate_image` | boolean | No | `false` | Try 0/90/180/270 rotations for non-upright faces |
| `save_api_request` | boolean | No | `true` | Save in Business Console |
| `vendor_data` | string | No | — | Your identifier for session tracking |
### Example
```python
import requests
response = requests.post(
"https://verification.didit.me/v3/face-search/",
headers={"x-api-key": "YOUR_API_KEY"},
files={"user_image": ("photo.jpg", open("photo.jpg", "rb"), "image/jpeg")},
)
print(response.json())
```
```typescript
const formData = new FormData();
formData.append("user_image", photoFile);
const response = await fetch("https://verification.didit.me/v3/face-search/", {
method: "POST",
headers: { "x-api-key": "YOUR_API_KEY" },
body: formData,
});
```
### Response (200 OK)
```json
{
"request_id": "a1b2c3d4-...",
"face_search": {
"status": "Approved",
"total_matches": 1,
"matches": [
{
"session_id": "uuid-...",
"session_number": 1234,
"similarity_percentage": 95.2,
"vendor_data": "user-456",
"verification_date": "2025-06-10T10:30:00Z",
"user_details": {
"name": "Elena Martinez",
"document_type": "Identity Card",
"document_number": "***456"
},
"match_image_url": "https://example.com/match.jpg",
"status": "Approved",
"is_blocklisted": false
}
],
"user_image": {
"entities": [
{"age": "27.6", "bbox": [40, 40, 120, 120], "confidence": 0.95, "gender": "female"}
],
"best_angle": 0
},
"warnings": []
}
}
```
### Status Values & Handling
| Status | Meaning | Action |
|---|---|---|
| `"Approved"` | No concerning matches found | Proceed — new unique user |
| `"In Review"` | Matches above similarity threshold | Review `matches[]` for potential duplicates |
| `"Declined"` | Blocklist match or policy violation | Check `matches[].is_blocklisted` and `warnings` |
### Error Responses
| Code | Meaning | Action |
|---|---|---|
| `400` | Invalid request | Check file format, size, parameters |
| `401` | Invalid API key | Verify `x-api-key` header |
| `403` | Insufficient credits | Top up at business.didit.me |
---
## Response Field Reference
### Match Object
| Field | Type | Description |
|---|---|---|
| `session_id` | string | UUID of the matching session |
| `session_number` | integer | Session number |
| `similarity_percentage` | float | 0-100 similarity score |
| `vendor_data` | string | Your reference from the matching session |
| `verification_date` | string | ISO 8601 timestamp |
| `user_details.name` | string | Name from the matching session |
| `user_details.document_type` | string | Document type used |
| `user_details.document_number` | string | Partially masked document number |
| `match_image_url` | string | Temporary URL (expires **4 hours**) |
| `status` | string | Status of the matching session |
| `is_blocklisted` | boolean | Whether the match is from the blocklist |
### User Image Object
| Field | Type | Description |
|---|---|---|
| `entities[].age` | string | Estimated age |
| `entities[].bbox` | array | Face bounding box `[x1, y1, x2, y2]` |
| `entities[].confidence` | float | Detection confidence (0-1) |
| `entities[].gender` | string | `"male"` or `"female"` |
| `best_angle` | integer | Rotation applied (0, 90, 180, 270) |
---
## Warning Tags
### Auto-Decline
| Tag | Description |
|---|---|
| `NO_FACE_DETECTED` | No face found in image |
| `FACE_IN_BLOCKLIST` | Face matches a blocklisted entry |
### Configurable
| Tag | Description |
|---|---|
| `MULTIPLE_FACES_DETECTED` | Multiple faces detected — unclear which to use |
> **Similarity threshold** and **allow multiple faces** settings are configurable in Console.
Warning severity: `error` (→ Declined), `warning` (→ In Review), `information` (no effect).
---
## Common Workflows
### Duplicate Account Detection
```
1. During new user registration
2. POST /v3/face-search/ → {"user_image": selfie}
3. If total_matches == 0 → new unique user
If matches found → check similarity_percentage:
90%+ → likely duplicate, investigate matches[].vendor_data
70-89% → possible match, flag for manual review
```
### Combined Verification + Dedup
```
1. POST /v3/passive-liveness/ → verify user is real
2. POST /v3/face-search/ → check for existing accounts
3. POST /v3/id-verification/ → verify identity document
4. POST /v3/face-match/ → compare selfie to document photo
5. All Approved → verified, unique, real user
```
> **Security:** Match image URLs expire after 4 hours. Store only `session_id` and `similarity_percentage` — minimize biometric data on your servers.
---
## Utility Scripts
**search_faces.py**: Search for matching faces from the command line.
```bash
# Requires: pip install requests
export DIDIT_API_KEY="your_api_key"
python scripts/search_faces.py selfie.jpg
python scripts/search_faces.py photo.png --rotate --vendor-data user-123
```
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
License: MIT
Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
Version reported in registry metadata; check source releases before relying on it.
Quality
55/100
Promising
Trust
56/100
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
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"alternative_skills": [
{
"slug": "yanliudesign-mono-color-skill",
"name": "mono-color",
"url": "https://www.openagentskill.com/skills/yanliudesign-mono-color-skill",
"stars": 1919,
"install_command": "npx skills add yanliudesign/mono-color-skill --skill mono-color",
"trust_score": 85,
"audit_score": 93
}
],
"do_not_use_when": [
"teams that need a vendor-supported SLA",
"production agents without a repository review",
"Low GitHub adoption signal",
"The utility script search_faces.py references 'similarity' in the output, but the API response uses 'similarity_percentage'. This will cause incorrect display of match scores.",
"No OpenAgentSkill engagement data yet",
"High-risk permission hints: Shell or command execution, Secrets or environment access",
"Dependency or permission surface needs review",
"Permission surface may require sandboxing"
],
"agent_contract": {
"task_input": "Use didit-face-search in an agent workflow",
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
"install_policy": "block",
"minimum_review_before_use": [
"Trust: 64/100 Manual review",
"Audit: 68/100 Needs review",
"Safety: 24/100 Avoid automatic install",
"Review repository, license, install command, and permission surface before production use."
],
"expected_agent_output": {
"selected_skill": "didit-protocol-didit-face-search (didit-face-search)",
"install_command": "npx skills add didit-protocol/skills --skill didit-face-search",
"risk_summary": "Needs review; Blocked for auto-install; Review before production",
"verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
}
},
"outcome_feedback": {
"endpoint": "https://www.openagentskill.com/api/agent/outcome",
"method": "POST",
"requires_resolve_event_id": true,
"event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
"expected_outcomes": [
"success",
"failed",
"not_relevant",
"blocked_by_risk",
"setup_required"
],
"payload_template": {
"event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
"skill_slug": "didit-protocol-didit-face-search",
"task": "Use didit-face-search in an agent workflow",
"agent": "codex",
"outcome": "success",
"install_used": true,
"risk_blocked": false,
"setup_required": false,
"task_success": true,
"output_quality": 4,
"error_type": null,
"human_review_required": false,
"workspace": "sandbox",
"time_to_useful_ms": 120000,
"notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
}
},
"endpoints": {
"web": "https://www.openagentskill.com/skills/didit-protocol-didit-face-search",
"api": "https://www.openagentskill.com/api/agent/skills/didit-protocol-didit-face-search",
"audit": "https://www.openagentskill.com/skills/didit-protocol-didit-face-search/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=didit-protocol-didit-face-search&task=Use%20didit-face-search%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20didit-face-search%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20didit-face-search%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/didit-protocol-didit-face-search/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/didit-protocol-didit-face-search"
}
}Listing source
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Do not auto-install
Audit
68/100
Needs review
Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.