Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Developer Tools
Didit Face Match
Compare two facial images using Didit Face Match API to verify identity by returning a similarity score with optional rotation and multi-face detection.
skill openclawclawhub Free
Compare two facial images using Didit Face Match API to verify identity by returning a similarity score with optional rotation and multi-face detection.
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/match_faces.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.3.0
Provenance
- Publisher
- rosasalberto
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Overview
Compares two facial images to determine if they belong to the same person. Returns a similarity score (0-100). Key constraints: Supported formats: JPEG, PNG, WebP, TIFF Maximum file size: 5MB per image If multiple faces in an image, the largest face is used for comparison Both user_image and ref_image are required Capabilities: Similarity scoring, age estimation, gender detection, face bounding boxes, configurable decline threshold, optional image rotation for non-upright faces. API Reference: https://docs.didit.me/standalone-apis/face-match Feature Guide: https://docs.didit.me/core-technology/face-match/overview
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: Register: POST https://apx.didit.me/auth/v2/programmatic/register/ with {"email": "you@gmail.com", "password": "MyStr0ng!Pass"} Check email for a 6-character OTP code 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-match/
Headers
HeaderValueRequiredx-api-keyYour API keyYesContent-Typemultipart/form-dataYes
Request Parameters (multipart/form-data)
ParameterTypeRequiredDefaultConstraintsDescriptionuser_imagefileYes—JPEG/PNG/WebP/TIFF, max 5MBUser's face image to verifyref_imagefileYes—Same as aboveReference image to compare againstface_match_score_decline_thresholdintegerNo300-100Scores below this = Declinedrotate_imagebooleanNofalse—Try 0/90/180/270 degree rotations to find upright facesave_api_requestbooleanNotrue—Save in Business Console Manual Checksvendor_datastringNo——Your identifier for session tracking
Example
import requests response = requests.post( "https://verification.didit.me/v3/face-match/", headers={"x-api-key": "YOUR_API_KEY"}, files={ "user_image": ("selfie.jpg", open("selfie.jpg", "rb"), "image/jpeg"), "ref_image": ("id_photo.jpg", open("id_photo.jpg", "rb"), "image/jpeg"), }, data={"face_match_score_decline_threshold": "50"}, ) const formData = new FormData(); formData.append("user_image", selfieFile); formData.append("ref_image", referenceFile); formData.append("face_match_score_decline_threshold", "50"); const response = await fetch("https://verification.didit.me/v3/face-match/", { method: "POST", headers: { "x-api-key": "YOUR_API_KEY" }, body: formData, });
Response (200 OK)
{ "request_id": "a1b2c3d4-...", "face_match": { "status": "Approved", "score": 80, "user_image": { "entities": [ {"age": 27.63, "bbox": [40, 40, 100, 100], "confidence": 0.717, "gender": "male"} ], "best_angle": 0 }, "ref_image": { "entities": [ {"age": 22.16, "bbox": [156, 234, 679, 898], "confidence": 0.717, "gender": "male"} ], "best_angle": 0 }, "warnings": [] }, "created_at": "2025-05-01T13:11:07.977806Z" }
Status Values & Handling
StatusMeaningAction"Approved"Score >= thresholdFaces match — proceed"Declined"Score < threshold or no faceCheck warnings for details. May need better image"In Review"Needs manual reviewWait for review or retrieve via session API
Error Responses
CodeMeaningAction400Invalid requestCheck file format, size, parameters401Invalid API keyVerify x-api-key header403Insufficient creditsTop up at business.didit.me
Response Field Reference
FieldTypeDescriptionstatusstring"Approved", "Declined", "In Review"scoreinteger0-100 similarity score (higher = more similar). null if no face foundentities[].agefloatEstimated ageentities[].bboxarrayFace bounding box [x1, y1, x2, y2]entities[].confidencefloatFace detection confidence (0-1)entities[].genderstring"male" or "female"best_angleintegerBest rotation angle for the facewarningsarray{risk, log_type, short_description, long_description}
Warning Tags
TagDescriptionAuto-DeclineNO_REFERENCE_IMAGEReference or face image missingYesNO_FACE_DETECTEDNo face detected in one or both imagesYesLOW_FACE_MATCH_SIMILARITYScore below threshold — potential identity mismatchConfigurable Security best practice: Only store the status and score. Minimize biometric image data on your servers. Image URLs (in workflow mode) expire after 60 minutes.
Score Interpretation
Score RangeInterpretationAction90-100Very high confidence — same personAuto-approve70-89High confidence — likely same personApprove (default threshold 30)50-69Moderate — possible matchConsider manual review30-49Low — likely different peopleDeclined at default threshold0-29Very low — different peopleDeclined
Utility Scripts
export DIDIT_API_KEY="your_api_key" python scripts/match_faces.py selfie.jpg id_photo.jpg python scripts/match_faces.py selfie.jpg id_photo.jpg --threshold 50 --rotate
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Scripts
- SKILL.md
- scripts/match_faces.py