ProjectLens

Developer API

Live API Playground

Programmatically interact with the ProjectLens autonomous AI subnet. Submit audits, extract granular evidence chains, and build deterministic UI on top.

OpenAPI 3.1 CompatibleREST APIJSON

99.9%

Uptime

3

AI Agents

24

Evidence Sources

18s

Avg Runtime

Official SDKs

JavaScript

npm install projectlens-sdk

Python

pip install projectlens

Global Rate Limits

  • API Quota 100 req/min
  • File Upload 10 MB max
  • PDF Processing 20 pages max

Endpoints

POST/api/v1/analyze
v1.2.0

Authentication

Authorization: Bearer YOUR_API_KEY

Payload Parameters

FieldTypeDescription
github_urlstringRepository URL to clone & scan (Required)
docs_urlstringDocumentation URL (Optional)
whitepaper_pdffileOptional PDF encoded as Base64
deep_scanbooleanEnables extended AST tracing

cURL Example

curl -X POST https://api.projectlens.ai/v1/analyze \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "github_url": "https://github.com/project/repo",
    "docs_url": "https://docs.project.com",
    "deep_scan": true
  }'

Average Response Time

18 – 35s

Due to deep agent logic overhead, asynchronous webhook pinging is highly recommended.

Webhook / Async Flow

POST /api/v1/analyze

↳ returns {"report_id": "xyz"}

GET /api/v1/report/{id}

↳ returns {"status": "completed", ...}

Successful Response

{
  "status": "success",
  "data": {
    "report_id": "94a3-7bf1-22cd",
    "score": 94,
    "agents_deployed": 3,
    "confidence_interval": "high",
    "risks": [],
    "evidence_chain": [
      {
        "evidence_id": "ev_01H8XDKP",
        "source": "GitHub",
        "validated": true
      }
    ]
  }
}

HTTP Status Codes

200OK
400Bad Request
404Source Not Found
429Rate Limited
500Server Error

Response Schema

Report
├── score (0-100)
├── findings
│   ├── strengths[]
│   └── weaknesses[]
├── evidence_chain
│   ├── source_hash
│   └── validated
├── confidence
└── recommendations