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rosasalberto

Didit Kyc Onboarding

by Didit · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install didit-kyc-onboarding
Description
End-to-end KYC (Know Your Customer) identity verification for onboarding real users. Use when someone needs to perform KYC, onboard users with identity verif...
README (SKILL.md)

Running KYC with Didit

End-to-end Know Your Customer (KYC) verification. This skill creates a KYC workflow, generates a session URL where a real user completes ID scan + selfie + face match, and retrieves the verification decision.

What the user experiences:

  1. Receives a verification link
  2. Scans their ID document (passport, ID card, driver's license)
  3. Takes a live selfie
  4. System auto-matches selfie to document photo
  5. Gets approved, declined, or flagged for review

API Reference:


Authentication

All requests require x-api-key header. Get your key from Didit Business Console → 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": "[email protected]", "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": "[email protected]", "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).


Quick Start — KYC in 3 API Calls

import requests, time

API_KEY = "your_api_key"
headers = {"x-api-key": API_KEY, "Content-Type": "application/json"}
BASE = "https://verification.didit.me/v3"

# 1. Create a KYC workflow (one-time setup — reuse the workflow_id for all users)
workflow = requests.post(f"{BASE}/workflows/", headers=headers, json={
    "workflow_label": "KYC Onboarding",
    "workflow_type": "kyc",
    "is_liveness_enabled": True,
    "is_face_match_enabled": True,
    "face_match_score_decline_threshold": 50,
    "max_retry_attempts": 3,
}).json()
workflow_id = workflow["uuid"]

# 2. Create a session for a specific user
session = requests.post(f"{BASE}/session/", headers=headers, json={
    "workflow_id": workflow_id,
    "vendor_data": "user-abc-123",
    "callback": "https://yourapp.com/verification-done",
    "language": "en",
}).json()

print(f"Send user to: {session['url']}")
# User opens this URL → scans ID → takes selfie → done

# 3. Poll for the decision (or use webhooks)
while True:
    decision = requests.get(
        f"{BASE}/session/{session['session_id']}/decision/",
        headers={"x-api-key": API_KEY},
    ).json()
    status = decision["status"]
    if status in ("Approved", "Declined", "In Review"):
        break
    time.sleep(10)

print(f"Result: {status}")
if status == "Approved":
    id_data = decision["id_verifications"][0]
    print(f"Name: {id_data['first_name']} {id_data['last_name']}")
    print(f"DOB: {id_data['date_of_birth']}")
    print(f"Document: {id_data['document_type']} ({id_data['issuing_country']})")

Step 1: Create a KYC Workflow

A workflow defines what checks run. Create one per use case and reuse it for all users.

POST https://verification.didit.me/v3/workflows/

API Reference: https://docs.didit.me/management-api/workflows/create

Recommended KYC Configuration

Parameter Value Why
workflow_type "kyc" Full KYC template with ID + selfie
is_liveness_enabled true Prevents spoofing (printed photos, screens)
is_face_match_enabled true Compares selfie to document photo
face_match_score_decline_threshold 50 Match below 50% → auto-decline
is_aml_enabled false Set true for sanctions/PEP screening (+cost)
max_retry_attempts 3 User can retry 3 times on failure

Response

{
  "uuid": "d8d2fa2d-c69c-471c-b7bc-bc71512b43ef",
  "workflow_label": "KYC Onboarding",
  "workflow_type": "kyc",
  "features": ["ocr", "liveness", "face_match"],
  "total_price": "0.10",
  "workflow_url": "https://verify.didit.me/..."
}

Save uuid as your workflow_id.


Step 2: Create a Session for Each User

Each user gets their own session. The session generates a unique URL where they complete verification.

POST https://verification.didit.me/v3/session/

API Reference: https://docs.didit.me/sessions-api/create-session

Key Parameters

Parameter Type Required Description
workflow_id uuid Yes From Step 1
vendor_data string Recommended Your user ID — links the session to your system
callback url Recommended Redirect URL after verification. Didit appends ?verificationSessionId=...&status=...
language string No UI language (ISO 639-1). Auto-detected if omitted
contact_details.email string No Pre-fill email for notification
expected_details.first_name string No Triggers mismatch warning if document name differs
expected_details.date_of_birth string No YYYY-MM-DD format
metadata JSON string No Custom data stored with session

Response

{
  "session_id": "11111111-2222-3333-4444-555555555555",
  "session_token": "abcdef123456",
  "url": "https://verify.didit.me/session/abcdef123456",
  "status": "Not Started",
  "workflow_id": "d8d2fa2d-..."
}

Send the user to url — this is where they complete verification (web or mobile).


Step 3: Get the Decision

After the user completes verification, retrieve the results.

GET https://verification.didit.me/v3/session/{sessionId}/decision/

API Reference: https://docs.didit.me/sessions-api/retrieve-session

Two Ways to Know When It's Ready

Option A: Webhooks (recommended for production) Configure a webhook URL in Business Console → API & Webhooks. Didit sends a POST with session_id and status when the decision is ready.

Option B: Polling Poll GET /v3/session/{id}/decision/ every 10–30 seconds. Check status — stop when it's Approved, Declined, or In Review.

Decision Response Fields

{
  "session_id": "...",
  "status": "Approved",
  "features": ["ID_VERIFICATION", "LIVENESS", "FACE_MATCH"],
  "id_verifications": [{
    "status": "Approved",
    "document_type": "PASSPORT",
    "issuing_country": "USA",
    "first_name": "John",
    "last_name": "Doe",
    "date_of_birth": "1990-01-15",
    "document_number": "ABC123456",
    "expiry_date": "2030-06-01",
    "gender": "M",
    "nationality": "USA",
    "mrz": "P\x3CUSADOE\x3C\x3CJOHN\x3C\x3C\x3C\x3C\x3C\x3C\x3C\x3C\x3C..."
  }],
  "liveness_checks": [{
    "status": "Approved",
    "method": "PASSIVE",
    "score": 92.5
  }],
  "face_matches": [{
    "status": "Approved",
    "score": 97.3
  }],
  "aml_screenings": [],
  "warnings": []
}

Key Decision Statuses

Status Meaning Action
Approved All checks passed User is verified
Declined One or more checks failed Check warnings for details
In Review Borderline result Manual review needed, or auto-decide via API
Not Started User hasn't opened the link yet Wait or remind user
In Progress User is completing verification Wait
Expired Session expired (default: 7 days) Create a new session

Optional: Post-Decision Actions

Approve or Decline Manually

PATCH https://verification.didit.me/v3/session/{sessionId}/update-status/

API Reference: https://docs.didit.me/sessions-api/update-status

requests.patch(f"{BASE}/session/{session_id}/update-status/",
    headers=headers,
    json={"new_status": "Approved", "comment": "Manual review passed"})

Request Resubmission

If the ID photo was blurry, ask the user to redo just that step:

requests.patch(f"{BASE}/session/{session_id}/update-status/",
    headers=headers,
    json={
        "new_status": "Resubmitted",
        "nodes_to_resubmit": [{"node_id": "feature_ocr", "feature": "OCR"}],
        "send_email": True,
        "email_address": "[email protected]",
    })

Block Fraudulent Users

requests.post(f"{BASE}/blocklist/add/",
    headers=headers,
    json={"session_id": session_id, "blocklist_face": True, "blocklist_document": True})

API Reference: https://docs.didit.me/sessions-api/blocklist/add

Generate PDF Report

response = requests.get(f"{BASE}/session/{session_id}/generate-pdf",
    headers={"x-api-key": API_KEY})

API Reference: https://docs.didit.me/sessions-api/generate-pdf


KYC Workflow Variants

KYC + AML Screening

Add sanctions/PEP screening to catch high-risk individuals:

requests.post(f"{BASE}/workflows/", headers=headers, json={
    "workflow_type": "kyc",
    "is_liveness_enabled": True,
    "is_face_match_enabled": True,
    "is_aml_enabled": True,
    "aml_decline_threshold": 80,
})

KYC + Phone + Email

Add contact verification to the flow:

requests.post(f"{BASE}/workflows/", headers=headers, json={
    "workflow_type": "kyc",
    "is_liveness_enabled": True,
    "is_face_match_enabled": True,
    "is_phone_verification_enabled": True,
    "is_email_verification_enabled": True,
})

KYC + NFC (Chip Reading)

For passports with NFC chips — highest assurance:

requests.post(f"{BASE}/workflows/", headers=headers, json={
    "workflow_type": "kyc",
    "is_liveness_enabled": True,
    "is_face_match_enabled": True,
    "is_nfc_enabled": True,
})

Utility Scripts

run_kyc.py — Full KYC setup from the command line

# Requires: pip install requests
export DIDIT_API_KEY="your_api_key"

# Create a KYC workflow (one-time)
python scripts/run_kyc.py setup --label "My KYC" --liveness --face-match

# Create a session for a user
python scripts/run_kyc.py session --workflow-id \x3Cuuid> --vendor-data user-123

# Get the decision
python scripts/run_kyc.py decision \x3Csession_id>

# Full flow: create workflow + session in one command
python scripts/run_kyc.py full --vendor-data user-123 --callback https://myapp.com/done

Can also be imported:

from scripts.run_kyc import setup_kyc_workflow, create_kyc_session, get_decision
Usage Guidance
This skill appears coherent, but KYC handles sensitive personal data — verify that 'didit.me' is the provider you intend to use and review their privacy/security policies and billing terms before sending real user data. Use a dedicated Didit API key for testing (don't reuse high-privilege production keys), store keys securely, and ensure any callback URL you supply is served over HTTPS and protected (to avoid leaking verification results). If you plan to use programmatic registration, create test accounts and rotate/delete keys when done. Finally, confirm pricing and compliance (data residency, retention, and consent) for your jurisdiction before onboarding real users.
Capability Analysis
Type: OpenClaw Skill Name: didit-kyc-onboarding Version: 1.0.0 The OpenClaw skill bundle for 'didit-kyc-onboarding' is benign. The `SKILL.md` provides clear documentation and instructions for integrating with the Didit KYC API, including setup steps for obtaining an API key and managing billing, which are presented as user actions, not agent directives. The `scripts/run_kyc.py` script acts as a legitimate client for the Didit API, correctly using environment variables for API keys and communicating exclusively with the `didit.me` domain. No evidence of prompt injection, data exfiltration, unauthorized execution, persistence mechanisms, or other malicious intent was found in either the documentation or the Python script.
Capability Assessment
Purpose & Capability
Name/description match the included SKILL.md and script: both create workflows, sessions, and retrieve decisions from Didit. The single required env var (DIDIT_API_KEY) is exactly what this integration needs.
Instruction Scope
SKILL.md and the Python script only call Didit domains (verification.didit.me, apx.didit.me) and describe expected KYC flows. There are no instructions to read unrelated local files, other env vars, or to exfiltrate data to third parties. The programmatic registration step (email/password + OTP) is part of obtaining an API key and is documented.
Install Mechanism
There is no install spec; the skill is instruction + a small Python script. Nothing is downloaded from arbitrary URLs and no installers run. This is low-risk from an install-mechanism perspective.
Credentials
Only the DIDIT_API_KEY is required and used. The script checks for that env var and exits if absent. No unrelated credentials, secret patterns, or system config paths are requested.
Persistence & Privilege
The skill is not forced-always, has no special permanence flags, and does not modify other skills or system-wide settings. It runs on-demand and only performs network calls to the service it integrates with.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install didit-kyc-onboarding
  3. After installation, invoke the skill by name or use /didit-kyc-onboarding
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
End-to-end KYC onboarding flow: workflow creation, session generation, decision retrieval
Metadata
Slug didit-kyc-onboarding
Version 1.0.0
License
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Didit Kyc Onboarding?

End-to-end KYC (Know Your Customer) identity verification for onboarding real users. Use when someone needs to perform KYC, onboard users with identity verif... It is an AI Agent Skill for Claude Code / OpenClaw, with 292 downloads so far.

How do I install Didit Kyc Onboarding?

Run "/install didit-kyc-onboarding" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Didit Kyc Onboarding free?

Yes, Didit Kyc Onboarding is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Didit Kyc Onboarding support?

Didit Kyc Onboarding is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Didit Kyc Onboarding?

It is built and maintained by Didit (@rosasalberto); the current version is v1.0.0.

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