Polymarket Emerging Tech Trader

Trades Polymarket prediction markets on Web3/DeFi milestones, NFT market recovery, metaverse adoption, humanoid robotics deployments, quantum computing breakthroughs, and synthetic biology commercialization. Use when you want to capture alpha on niche emerging technology markets where most retail traders lack domain expertise.

Emerging Tech Trader

This is a template.
The default signal is keyword discovery + on-chain data signals — remix it with DeFiLlama TVL feeds, GitHub commit velocity for quantum computing projects, robotics deployment trackers, or synthetic biology investment databases.
The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Emerging tech markets are among the highest-edge opportunities on Polymarket because most retail participants lack domain expertise. A trader with genuine technical knowledge in robotics, quantum computing, or DeFi holds massive informational advantage.

This skill covers 5 sub-categories:

1. Web3 & DeFi

• Prediction market TVL milestones, cross-chain liquidity thresholds
• NFT market recovery volume markers
• Tokenized prediction position collateral milestones

2. Metaverse & VR/AR

• Meta Horizon DAU milestones, VR headset sales
• Virtual real estate transaction volumes

3. Robotics & Automation

• Humanoid robot factory deployments (Figure, Tesla Optimus, 1X)
• Autonomous delivery robot counts
• Warehouse automation penetration rates

4. Quantum Computing

• IBM qubit count milestones
• Commercial quantum revenue thresholds
• Quantum advantage demonstrations

5. Synthetic Biology

• Lab-grown meat regulatory approvals
• Precision fermentation market size
• Engineered bacteria commercial deployments

Signal Logic

Default Signal: Conviction-Based Sizing with Hype-Cycle Bias

1. Discover markets matching emerging tech keywords
2. Compute base conviction from distance to threshold (0% at boundary → 100% at p=0/p=1)
3. Apply domain_bias() multiplier — boost underappreciated domains, dampen hype-prone ones
4. Size = max(MIN_TRADE, conviction × bias × MAX_POSITION) — capped at MAX_POSITION
5. Skip markets with spread > MAX_SPREAD or fewer than MIN_DAYS to resolution

Domain Bias (built-in, no API required)

Different emerging tech categories have systematic mispricing patterns. domain_bias() adjusts conviction based on known retail behavior in each domain:

Domain	Bias	Why
Metaverse / NFT	0.70x	Media hype cycles inflate YES; most milestones miss
Humanoid robots	0.75x	YouTube demos precede real deployments by 6–18 months
Quantum computing	1.30x	arXiv progress is systematic; markets lag by weeks
Synthetic biology	1.25x	Regulatory filings are public; market underweights precedent
DeFi / TVL	1.20x	On-chain data is real-time; market repricing lags 2–6h
Other	1.00x	No systematic bias detected

Example: quantum market at 25% → conviction 34% × 1.3x = 44% → $11 position. Metaverse market at same price → 34% × 0.7x = 24% → $6 (conservative).

Remix Ideas

• DeFiLlama API: Replace market.current_probability with TVL-implied probability — trade the divergence between on-chain data and market price
• GitHub API: Measure commit velocity on IBM Qiskit / Google Cirq repos as quantum progress signal
• CoinGlass / OpenSea: NFT floor and volume data as leading indicator for NFT milestone markets
• The Good Food Institute: Lab-grown meat regulatory tracker for synthetic biology markets
• arXiv API: Monitor quantum/ML paper releases as leading signal before market repricing

Market Categories Tracked

KEYWORDS = [
    'Web3', 'DeFi', 'NFT', 'blockchain', 'metaverse', 'VR', 'AR',
    'robot', 'humanoid', 'autonomous delivery', 'Boston Dynamics',
    'Tesla Optimus', 'Figure robot', 'warehouse automation',
    'quantum', 'qubit', 'IBM quantum', 'Google quantum',
    'synthetic biology', 'lab-grown meat', 'cultivated meat',
    'precision fermentation', 'Solana', 'Ethereum', 'TVL',
]

Risk Parameters

Parameter	Default	Notes
Max position size	$25 USDC	Emerging tech markets are volatile
Min market volume	$2,000	Some niche markets start illiquid
Max bid-ask spread	15%	Accept wider spreads for edge markets
Min days to resolution	14	Technical milestones need longer lead time
Max open positions	8	Diversify across sub-categories

Sub-Category Edge Analysis

Category	Edge Source	Typical Market Bias
Quantum Computing	Academic paper lag (arXiv 6–24h before news)	Retail underestimates IBM progress
Humanoid Robots	YouTube demo videos precede deployments	Fan hype overprices Tesla Optimus
DeFi/TVL	On-chain data is real-time	Markets lag DeFiLlama by 2–6h
Lab-Grown Meat	Regulatory filings public before decisions	Market underweights FDA precedent
NFT Markets	OpenSea/Blur volume APIs	Volume data available before price consensus

Key Data Sources

• DeFiLlama: https://defillama.com/
• GitHub API: https://api.github.com/
• IBM Quantum Network: https://quantum.ibm.com/
• The Good Food Institute: https://gfi.org/
• CoinGlass NFT: https://www.coinglass.com/nft

Installation & Setup

clawhub install polymarket-emerging-tech-trader

Requires: SIMMER_API_KEY environment variable.

Cron Schedule

Runs every 15 minutes (*/15 * * * *). Emerging tech events are infrequent but high-impact when they occur.

Safety & Execution Mode

The skill defaults to paper trading (venue="sim"). Real trades only execute when --live is passed explicitly.

Scenario	Mode	Financial risk
python trader.py	Paper (sim)	None
Cron / automaton	Paper (sim)	None
python trader.py --live	Live (polymarket)	Real USDC

The automaton cron is set to null — it does not run on a schedule until you configure it in the Simmer UI. autostart: false means it won't start automatically on install.

Required Credentials

Variable	Required	Notes
SIMMER_API_KEY	Yes	Trading authority — keep this credential private. Do not place a live-capable key in any environment where automated code could call --live.

Tunables (Risk Parameters)

All risk parameters are declared in clawhub.json as tunables and adjustable from the Simmer UI without code changes. They use SIMMER_-prefixed env vars so apply_skill_config() can load them securely.

Variable	Default	Purpose
SIMMER_MAX_POSITION	25	Max USDC per trade (reached at 100% conviction)
SIMMER_MIN_VOLUME	2000	Min market volume filter (USD)
SIMMER_MAX_SPREAD	0.15	Max bid-ask spread (0.15 = 15%)
SIMMER_MIN_DAYS	14	Min days until market resolves
SIMMER_MAX_POSITIONS	8	Max concurrent open positions
SIMMER_YES_THRESHOLD	0.38	Buy YES if market price ≤ this value
SIMMER_NO_THRESHOLD	0.62	Sell NO if market price ≥ this value
SIMMER_MIN_TRADE	5	Floor for any trade (min USDC regardless of conviction)

Dependency

simmer-sdk is published on PyPI by Simmer Markets.

• PyPI: https://pypi.org/project/simmer-sdk/
• GitHub: https://github.com/SpartanLabsXyz/simmer-sdk
• Publisher: [e-mail]

Review the source before providing live credentials if you require full auditability.