Molt Sift

Validate and extract high-confidence signals from JSON, text, or streams using customizable rules, with schema validation and integrated Solana bounty payments.

Sift through the sand. Find the signal. Get paid.

Quick Start

CLI Usage

bash

# Validate JSON against a schema
molt-sift validate --input data.json --schema schema.json

# Sift text output for quality signals
molt-sift sift --input output.txt --rules crypto

# Run a bounty validation job
molt-sift bounty claim --job-id abc123 --payout-address YOUR_SOLANA_ADDRESS

As a Library

python

from molt_sift import Sifter

sifter = Sifter(rules="crypto")
result = sifter.validate(raw_data, schema)
print(result)  # {score: 0.92, clean: {...}, issues: [...]}

Core Features

1. Validate Against Schema

• Input: raw JSON/text + validation rules
• Output: cleaned data + quality score (0-1)
• Use for: ensuring outputs match expected structure

2. Sift for Signal

• Input: noisy data + signal rules (e.g., "crypto", "trading", "sentiment")
• Output: high-confidence entries + scores
• Use for: filtering Polymarket trade signals, memecoin radar, etc.

3. Bounty Mode

• Accept PayAClaw/MoltyGuild bounty jobs
• Validate input → return cleaned output
• Auto-trigger x402 payment on completion
• Use for: passive income while handling other tasks

4. Quality Scoring

• Structural integrity (valid JSON, required fields)
• Data completeness (% fields filled)
• Consistency (no contradictions, valid types)
• Confidence (signal strength if applicable)
• Overall score: 0-100%

Bounty Integration (Phase 1 - Fully Implemented)

For Bounty Hunters: Claim & Earn

Start a bounty hunting agent that automatically claims and processes validation jobs:

bash

# Start watching PayAClaw for bounty jobs
molt-sift bounty claim --auto --payout YOUR_SOLANA_ADDRESS

# Example output:
# [BountyAgent] 🦀 Starting bounty agent (watching PayAClaw)...
# [BountyAgent] Agent ID: agent_1234567890
# [BountyAgent] Payout address: YOUR_SOLANA_ADDRESS
# [BountyAgent] Status: ACTIVE
#
# [BountyAgent] Check #1 - Found 2 available bounty(ies)
# [BountyAgent] Auto-claiming: Validate crypto data ($5.00)
# [BountyAgent] ✓ Claimed job molt_sift_001
# [BountyAgent] Processing job molt_sift_001...
# [BountyAgent] Validating data with rule set: crypto
# [BountyAgent] Validation score: 0.85
# [BountyAgent] ✓ Result submitted
# [BountyAgent] Triggering payment of $5.00 USDC...
# [BountyAgent] ✓ Payment initiated
# [BountyAgent] Transaction: abc123def456...

The agent will:

1. Watch PayAClaw for available "Molt Sift" bounty jobs
2. Auto-claim matching validation jobs
3. Process data with Sifter engine
4. Submit results back to PayAClaw
5. Receive USDC payment via x402 Solana escrow

For Bounty Posters: Create & Pay

Post validation bounties via HTTP API:

bash

# Start the API server
molt-sift api start --port 8000

# In another terminal, post a bounty:
curl -X POST http://localhost:8000/bounty \
  -H "Content-Type: application/json" \
  -d '{
    "raw_data": {
      "symbol": "BTC",
      "price": 42850.50,
      "volume": 1500000000,
      "timestamp": "2026-02-25T12:00:00Z"
    },
    "schema": {
      "type": "object",
      "required": ["symbol", "price"],
      "properties": {
        "symbol": {"type": "string"},
        "price": {"type": "number"},
        "volume": {"type": "number"}
      }
    },
    "validation_rules": "crypto",
    "amount_usdc": 5.00,
    "payout_address": "AGENT_SOLANA_ADDRESS"
  }'

Response:

json

{
  "status": "validated",
  "validation_score": 0.92,
  "clean_data": {
    "symbol": "BTC",
    "price": 42850.50,
    "volume": 1500000000,
    "timestamp": "2026-02-25T12:00:00Z"
  },
  "issues": [],
  "payment_status": "initiated",
  "payment_txn": "5AbcDef123456GhIjK789LmNoPqRsTuVwXyZ0",
  "amount_paid_usdc": 5.00,
  "explorer_url": "https://solscan.io/tx/5AbcDef123456GhIjK789LmNoPqRsTuVwXyZ0?cluster=mainnet-beta"
}

API Endpoints

Health Check:

bash

curl http://localhost:8000/health
# {"status": "healthy", "timestamp": "2026-02-25T12:00:00Z"}

Post Bounty:

bash

POST /bounty
Content-Type: application/json

{
  "raw_data": {...},           # Data to validate
  "schema": {...},              # JSON schema (optional)
  "validation_rules": "crypto", # Rule set: crypto, trading, sentiment, json-strict
  "amount_usdc": 5.00,          # Bounty reward
  "payout_address": "..."       # Recipient Solana address
}

Get Job Status:

bash

GET /bounty/<job_id>
# Returns job details and current status

Get Payment Status:

bash

GET /payment/<transaction_signature>
# Returns payment confirmation and blockchain status

Get Statistics:

bash

GET /stats
# Returns API statistics and volumes

Bounty Workflow

text

1. Agent A posts bounty: "Validate this crypto data"
   └─ Specifies data, validation rules, reward amount ($5)
   └─ Provides payout address

2. Agent B watches PayAClaw for bounties
   └─ Sees new "Molt Sift" job available
   └─ Auto-claims the job

3. Agent B validates with Molt Sift
   └─ Sifter processes data against rules
   └─ Returns score, cleaned data, issues found

4. Agent B submits results to PayAClaw
   └─ PayAClaw records the completion

5. Payment triggered via x402 Solana
   └─ USDC transfer initiated to Agent B's wallet
   └─ Transaction confirmed on-chain
   └─ Agent B receives payment

Earning Examples

Bounty Type: Crypto Data Validation

• Job: Validate price feed data
• Reward: $5 USDC
• Processing time: ~2 seconds
• Hourly rate: ~$9,000/hr

Bounty Type: Trading Order Validation

• Job: Validate order execution logs
• Reward: $3 USDC
• Processing time: ~1 second
• Hourly rate: ~$10,800/hr

Bounty Type: Sentiment Analysis

• Job: Extract and score sentiment
• Reward: $2 USDC
• Processing time: ~1 second
• Hourly rate: ~$7,200/hr

These are micro-transactions perfect for autonomous agents that can process many jobs in parallel.

Validation Rules

Pre-built rule sets for common domains:

• crypto: Price data, on-chain metrics, trading signals
• trading: Order books, execution logs, P&L
• sentiment: Text analysis, market mood
• json-strict: Structural validation only
• custom: User-defined rules

See references/rules.md for complete list and examples.

Architecture

text

molt-sift/
├── scripts/
│   ├── molt_sift.py      (CLI entry point)
│   ├── sifter.py         (core validation engine)
│   ├── bounty_agent.py   (PayAClaw integration)
│   └── api_server.py     (HTTP bounty endpoint)
├── references/
│   ├── rules.md          (validation rule definitions)
│   └── schemas.md        (common JSON schemas)
└── assets/
    └── templates/        (example inputs/outputs)

Getting Started

1. Install locally:

   bash

   pip install -e .
   

2. Test validation:

   bash

   molt-sift validate --input sample.json --schema crypto
   

3. Start bounty agent:

   bash

   molt-sift bounty claim --auto --payout YOUR_SOLANA_ADDR
   

4. Start API server:

   bash

   molt-sift api start --port 8000
   

Output Format

All results follow this structure:

json

{
  "status": "validated|sifted|failed",
  "score": 0.0-1.0,
  "clean_data": {...},
  "issues": [
    {
      "field": "price",
      "issue": "missing required value",
      "severity": "error|warning"
    }
  ],
  "metadata": {
    "rule_set": "crypto",
    "timestamp": "2026-02-25T12:00:00Z",
    "processing_ms": 125
  }
}

Deployment

Ready for:

• Local CLI
• Docker container (for API server)
• Cron jobs (batch validation)
• Real-time bounty hunting (subprocess)
• ClawHub integration

See references/deployment.md for setup guides.