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Estimates a person's age from a facial image via the Didit standalone API. Use when implementing age gating, checking if someone is over 18 or 21, performing age verification for compliance, or detecting underage users. Includes passive liveness check. Supports configurable thres
Estimates a person's age from a facial image via the Didit standalone API. Use when implementing age gating, checking if someone is over 18 or 21, performing age verification for compliance, or detecting underage users. Includes passive liveness check. Supports configurable thresholds, adaptive fallback to ID verification, and per-country restrictions.
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Estimates a person's age from a facial image using deep learning. Also performs a passive liveness check to prevent spoofing.
Key constraints:
Capabilities: Age estimation with confidence scoring, gender estimation, passive liveness detection, configurable age thresholds, per-country age restrictions, adaptive mode with ID verification fallback for borderline cases.
Liveness methods (workflow mode):
| Method | Security | Best For |
|---|---|---|
ACTIVE_3D (Action + Flash) | Highest | Banking, government, healthcare |
FLASHING (3D Flash) | High | Financial services, identity verification |
PASSIVE (single-frame CNN) | Standard | Low-friction consumer apps |
API Reference: https://docs.didit.me/standalone-apis/age-estimation Feature Guide: https://docs.didit.me/core-technology/age-estimation/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/age-estimation/
| 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 | — | Facial image (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 Manual Checks |
vendor_data | string | No | — | Your identifier for session tracking |
import requests
response = requests.post(
"https://verification.didit.me/v3/age-estimation/",
headers={"x-api-key": "YOUR_API_KEY"},
files={"user_image": ("selfie.jpg", open("selfie.jpg", "rb"), "image/jpeg")},
data={"vendor_data": "user-123"},
)
print(response.json())
const formData = new FormData();
formData.append("user_image", selfieFile);
const response = await fetch("https://verification.didit.me/v3/age-estimation/", {
method: "POST",
headers: { "x-api-key": "YOUR_API_KEY" },
body: formData,
});
{
"request_id": "a1b2c3d4-...",
"liveness": {
"status": "Approved",
"method": "PASSIVE",
"score": 89.92,
"age_estimation": 24.3,
"reference_image": "https://example.com/reference.jpg",
"video_url": null,
"warnings": []
},
"created_at": "2025-05-01T13:11:07.977806Z"
}
| Status | Meaning | Action |
|---|---|---|
"Approved" | Age verified above threshold, liveness passed | Proceed with your flow |
"Declined" | Age below minimum or liveness failed | Check warnings for specifics |
"In Review" | Borderline case, needs review | Trigger ID verification fallback or manual review |
| 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 |
|---|---|---|
status | string | "Approved", "Declined", "In Review", "Not Finished" |
method | string | "ACTIVE_3D", "FLASHING", or "PASSIVE" |
score | float | 0-100 liveness confidence score |
age_estimation | float | Estimated age in years (e.g. 24.3). null if no face |
reference_image | string | Temporary URL (expires 4 hours) |
video_url | string | Temporary URL for active liveness video. null for passive |
warnings | array | {risk, log_type, short_description, long_description} |
| Age Range | MAE (years) | Confidence |
|---|---|---|
| Under 18 | 1.5 | High |
| 18-25 | 2.8 | High |
| 26-40 | 3.2 | High |
| 41-60 | 3.9 | Medium-High |
| 60+ | 4.5 | Medium |
| Tag | Description |
|---|---|
NO_FACE_DETECTED | No face found in image |
LIVENESS_FACE_ATTACK | Spoofing attempt detected |
FACE_IN_BLOCKLIST | Face matches a blocklist entry |
| Tag | Description |
|---|---|
AGE_BELOW_MINIMUM | Estimated age below configured minimum |
AGE_NOT_DETECTED | Unable to estimate age (image quality, lighting) |
LOW_LIVENESS_SCORE | Liveness score below threshold |
POSSIBLE_DUPLICATED_FACE | Significant similarity with previously verified face |
Warning severity: error (→ Declined), warning (→ In Review), information (no effect).
1. Capture user selfie
2. POST /v3/age-estimation/ → {"user_image": selfie}
3. Check liveness.age_estimation >= your_minimum_age
4. If "Approved" → user meets age requirement
If "Declined" → check warnings for AGE_BELOW_MINIMUM or liveness failure
Build a workflow with an AGE_ESTIMATION feature (optionally followed by OCR for the ID verification fallback) so borderline ages trigger automatic ID verification.
1. POST /v3/workflows/ → {"workflow_label": "Adaptive Age", "features": [{"feature": "AGE_ESTIMATION"}, {"feature": "OCR"}]}
2. POST /v3/session/ → create session with the workflow_id from step 1
3. User takes selfie → system estimates age
4. Clear pass (well above threshold) → Approved instantly
Clear fail (well below threshold) → Declined
Borderline case → automatic ID verification fallback
5. If ID fallback triggered: per-country age restrictions apply
Configure in Console per issuing country:
| Country | Min Age | Overrides |
|---|---|---|
| USA | 18 | Mississippi: 21, Alabama: 19 |
| KOR | 19 | — |
| GBR | 18 | — |
| ARE | 21 | — |
Use "Apply age of majority" button in Console to auto-populate defaults.
estimate_age.py: Estimate age from a facial image via the command line.
# Requires: pip install requests
export DIDIT_API_KEY="your_api_key"
python scripts/estimate_age.py selfie.jpg
python scripts/estimate_age.py photo.png --threshold 21 --vendor-data user-123
name: didit-biometric-age-estimation
description: >
Estimates a person's age from a facial image via the Didit standalone API. Use when
implementing age gating, checking if someone is over 18 or 21, performing age verification
for compliance, or detecting underage users. Includes passive liveness check. Supports
configurable thresholds, adaptive fallback to ID verification, and per-country restrictions.
version: 1.1.0
metadata:
openclaw:
requires:
env:
- DIDIT_API_KEY
primaryEnv: DIDIT_API_KEY
emoji: "🎂"
homepage: https://docs.didit.me---
name: didit-biometric-age-estimation
description: >
Estimates a person's age from a facial image via the Didit standalone API. Use when
implementing age gating, checking if someone is over 18 or 21, performing age verification
for compliance, or detecting underage users. Includes passive liveness check. Supports
configurable thresholds, adaptive fallback to ID verification, and per-country restrictions.
version: 1.1.0
metadata:
openclaw:
requires:
env:
- DIDIT_API_KEY
primaryEnv: DIDIT_API_KEY
emoji: "🎂"
homepage: https://docs.didit.me
---
# Didit Age Estimation API
## Overview
Estimates a person's age from a facial image using deep learning. Also performs a passive liveness check to prevent spoofing.
**Key constraints:**
- Supported formats: **JPEG, PNG, WebP, TIFF**
- Maximum file size: **5MB**
- Image must contain **one clearly visible face**
- Accuracy: MAE ±3.5 years overall; ±1.5 years for under-18
**Capabilities:** Age estimation with confidence scoring, gender estimation, passive liveness detection, configurable age thresholds, per-country age restrictions, adaptive mode with ID verification fallback for borderline cases.
**Liveness methods (workflow mode):**
| Method | Security | Best For |
|---|---|---|
| `ACTIVE_3D` (Action + Flash) | Highest | Banking, government, healthcare |
| `FLASHING` (3D Flash) | High | Financial services, identity verification |
| `PASSIVE` (single-frame CNN) | Standard | Low-friction consumer apps |
**API Reference:** https://docs.didit.me/standalone-apis/age-estimation
**Feature Guide:** https://docs.didit.me/core-technology/age-estimation/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/age-estimation/
```
### 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** | — | Facial image (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 Manual Checks |
| `vendor_data` | string | No | — | Your identifier for session tracking |
### Example
```python
import requests
response = requests.post(
"https://verification.didit.me/v3/age-estimation/",
headers={"x-api-key": "YOUR_API_KEY"},
files={"user_image": ("selfie.jpg", open("selfie.jpg", "rb"), "image/jpeg")},
data={"vendor_data": "user-123"},
)
print(response.json())
```
```typescript
const formData = new FormData();
formData.append("user_image", selfieFile);
const response = await fetch("https://verification.didit.me/v3/age-estimation/", {
method: "POST",
headers: { "x-api-key": "YOUR_API_KEY" },
body: formData,
});
```
### Response (200 OK)
```json
{
"request_id": "a1b2c3d4-...",
"liveness": {
"status": "Approved",
"method": "PASSIVE",
"score": 89.92,
"age_estimation": 24.3,
"reference_image": "https://example.com/reference.jpg",
"video_url": null,
"warnings": []
},
"created_at": "2025-05-01T13:11:07.977806Z"
}
```
### Status Values & Handling
| Status | Meaning | Action |
|---|---|---|
| `"Approved"` | Age verified above threshold, liveness passed | Proceed with your flow |
| `"Declined"` | Age below minimum or liveness failed | Check `warnings` for specifics |
| `"In Review"` | Borderline case, needs review | Trigger ID verification fallback or manual review |
### 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
| Field | Type | Description |
|---|---|---|
| `status` | string | `"Approved"`, `"Declined"`, `"In Review"`, `"Not Finished"` |
| `method` | string | `"ACTIVE_3D"`, `"FLASHING"`, or `"PASSIVE"` |
| `score` | float | 0-100 liveness confidence score |
| `age_estimation` | float | Estimated age in years (e.g. `24.3`). `null` if no face |
| `reference_image` | string | Temporary URL (expires 4 hours) |
| `video_url` | string | Temporary URL for active liveness video. `null` for passive |
| `warnings` | array | `{risk, log_type, short_description, long_description}` |
### Accuracy by Age Range
| Age Range | MAE (years) | Confidence |
|---|---|---|
| Under 18 | 1.5 | High |
| 18-25 | 2.8 | High |
| 26-40 | 3.2 | High |
| 41-60 | 3.9 | Medium-High |
| 60+ | 4.5 | Medium |
---
## Warning Tags
### Auto-Decline
| Tag | Description |
|---|---|
| `NO_FACE_DETECTED` | No face found in image |
| `LIVENESS_FACE_ATTACK` | Spoofing attempt detected |
| `FACE_IN_BLOCKLIST` | Face matches a blocklist entry |
### Configurable (Decline / Review / Approve)
| Tag | Description |
|---|---|
| `AGE_BELOW_MINIMUM` | Estimated age below configured minimum |
| `AGE_NOT_DETECTED` | Unable to estimate age (image quality, lighting) |
| `LOW_LIVENESS_SCORE` | Liveness score below threshold |
| `POSSIBLE_DUPLICATED_FACE` | Significant similarity with previously verified face |
Warning severity: `error` (→ Declined), `warning` (→ In Review), `information` (no effect).
---
## Common Workflows
### Basic Age Gate
```
1. Capture user selfie
2. POST /v3/age-estimation/ → {"user_image": selfie}
3. Check liveness.age_estimation >= your_minimum_age
4. If "Approved" → user meets age requirement
If "Declined" → check warnings for AGE_BELOW_MINIMUM or liveness failure
```
### Adaptive Age Estimation (Workflow Mode)
Build a workflow with an `AGE_ESTIMATION` feature (optionally followed by `OCR` for the ID verification fallback) so borderline ages trigger automatic ID verification.
```
1. POST /v3/workflows/ → {"workflow_label": "Adaptive Age", "features": [{"feature": "AGE_ESTIMATION"}, {"feature": "OCR"}]}
2. POST /v3/session/ → create session with the workflow_id from step 1
3. User takes selfie → system estimates age
4. Clear pass (well above threshold) → Approved instantly
Clear fail (well below threshold) → Declined
Borderline case → automatic ID verification fallback
5. If ID fallback triggered: per-country age restrictions apply
```
### Per-Country Age Restrictions
Configure in Console per issuing country:
| Country | Min Age | Overrides |
|---|---|---|
| USA | 18 | Mississippi: 21, Alabama: 19 |
| KOR | 19 | — |
| GBR | 18 | — |
| ARE | 21 | — |
> Use "Apply age of majority" button in Console to auto-populate defaults.
---
## Utility Scripts
**estimate_age.py**: Estimate age from a facial image via the command line.
```bash
# Requires: pip install requests
export DIDIT_API_KEY="your_api_key"
python scripts/estimate_age.py selfie.jpg
python scripts/estimate_age.py photo.png --threshold 21 --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
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
53/100
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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"Financial research output is not financial advice; require human review before any live investment decision.",
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"installAttempts": 0,
"installSuccessRate": null,
"successRate": null,
"recentSuccessRate": null,
"recentFailureRate": null,
"riskBlocked": 0,
"setupRequired": 0,
"notRelevant": 0,
"avgOutputQuality": null,
"avgTimeToUsefulMs": null,
"productionOutcomes": 0,
"humanReviewRequired": 0,
"uniqueAgents": 0,
"lastOutcomeAt": null
},
"signals": [],
"penalties": [
"No real agent outcome evidence yet"
]
},
"audit": {
"score": 68,
"risk_level": "needs_review",
"risk_label": "Needs review",
"warnings": [
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"Financial research output is not financial advice; require human review before any live investment decision",
"The utility script `estimate_age.py` incorrectly parses the API response: it expects `result['age_estimation']` to be an object, but the API returns `result['liveness']['age_estimation']` as a float. This will cause a crash.",
"The script always sends `Content-Type: image/jpeg` regardless of the actual image format; should detect MIME type (e.g., using `mimetypes` or `imghdr`).",
"Low GitHub adoption signal",
"Financial research output is not financial advice; require human review before any live investment decision.",
"Quality score needs review"
]
},
"safety_gate": {
"tier": "blocked",
"label": "Blocked for auto-install",
"auto_install_policy": "block",
"auto_install_allowed": false,
"human_review_required": true,
"blocked": true,
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
},
"quality": {
"score": 55,
"label": "Promising"
},
"supply": {
"track": "Legal, policy, and compliance",
"scenario": "Security and compliance",
"maintenance": "1mo since push",
"risk": "Needs review"
},
"alternative_skills": [],
"do_not_use_when": [
"teams that need a vendor-supported SLA",
"production agents without a repository review",
"Low GitHub adoption signal",
"The utility script `estimate_age.py` incorrectly parses the API response: it expects `result['age_estimation']` to be an object, but the API returns `result['liveness']['age_estimation']` as a float. This will cause a crash.",
"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-biometric-age-estimation 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: 61/100 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-biometric-age-estimation (didit-biometric-age-estimation)",
"install_command": "npx skills add didit-protocol/skills --skill didit-biometric-age-estimation",
"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-biometric-age-estimation",
"task": "Use didit-biometric-age-estimation 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-biometric-age-estimation",
"api": "https://www.openagentskill.com/api/agent/skills/didit-protocol-didit-biometric-age-estimation",
"audit": "https://www.openagentskill.com/skills/didit-protocol-didit-biometric-age-estimation/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=didit-protocol-didit-biometric-age-estimation&task=Use%20didit-biometric-age-estimation%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20didit-biometric-age-estimation%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20didit-biometric-age-estimation%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/didit-protocol-didit-biometric-age-estimation/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/didit-protocol-didit-biometric-age-estimation"
}
}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.