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Polymarket Emerging Tech Trader
作者
diagnostikon
· GitHub ↗
· v0.0.3
· MIT-0
325
总下载
0
收藏
1
当前安装
5
版本数
在 OpenClaw 中安装
/install polymarket-emerging-tech-trader
功能描述
Trades Polymarket prediction markets on Web3/DeFi milestones, NFT market recovery, metaverse adoption, humanoid robotics deployments, quantum computing break...
安全使用建议
This skill is internally consistent with its stated purpose and appears safe to run in paper mode. Before enabling live trading: 1) Verify the simmer-sdk package origin/version (audit its PyPI page or vendor repo) to reduce supply-chain risk. 2) Use a SIMMER_API_KEY with minimal privileges (preferably a paper/sandbox key) and test thoroughly in sim mode. 3) Review trader.py's logic (already included) to confirm risk parameters match your appetite and adjust tunables. 4) Only enable --live after you trust the API provider and have confirmed no unexpected network endpoints. If you lack the ability to audit simmer-sdk, consider running the skill in an isolated environment or asking the publisher for provenance (homepage/source repo).
功能分析
Type: OpenClaw Skill
Name: polymarket-emerging-tech-trader
Version: 0.0.3
The skill bundle implements a legitimate Polymarket trading strategy for emerging technology markets. The Python code (trader.py) uses the simmer-sdk to execute trades, defaulting to a safe 'sim' (paper trading) mode unless explicitly run with a --live flag. The logic in SKILL.md and trader.py is transparent, focusing on conviction-based sizing and domain-specific bias without any evidence of data exfiltration, malicious execution, or prompt injection attacks.
能力标签
能力评估
Purpose & Capability
Name/description (Polymarket emerging tech trader) align with the code and SKILL.md. The skill only requests SIMMER_API_KEY and uses simmer_sdk to discover markets and place trades, which is expected for a trading agent. Tunables and keywords match the described market focus.
Instruction Scope
SKILL.md and trader.py instruct the agent to discover markets by keywords, compute conviction, and place trades via the SimmerClient. The skill explicitly defaults to paper trading (venue='sim') and requires an explicit --live flag for real trades. It does not instruct reading unrelated system files or unrelated credentials.
Install Mechanism
This is instruction-only with a declared pip dependency on 'simmer-sdk' in clawhub.json. There is no explicit install script or external download URL in the package. Note: installing runtime dependencies from PyPI (simmer-sdk) is normal but is a supply-chain vector — you should verify the package's provenance and version before granting it access to live credentials.
Credentials
The only required environment variable is SIMMER_API_KEY, which is appropriate for a trading client. However this API key grants trading capability; ensure the key's scope/permissions are limited (paper-only or restricted user) and rotate/regulate it. The script also reads multiple SIMMER_* tunables which are benign and documented in clawhub.json.
Persistence & Privilege
always:false and autostart:false (clawhub.json) — the skill is not force-included and won't run continuously unless the user enables it. automaton.managed with an entrypoint is normal for an operable skill. The agent can invoke the skill autonomously (platform default), which is expected; combine this with the prior note about key permissions before allowing live mode.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install polymarket-emerging-tech-trader - 安装完成后，直接呼叫该 Skill 的名称或使用
/polymarket-emerging-tech-trader触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v0.0.3
SDK resilience: try/except runt apply_skill_config
v0.0.2
fix: add _client.live=True so --live actually routes to polymarket-venue for real USDC trades
v1.0.2
Fix apply_skill_config AttributeError for new Simmer SDK compatibility
v1.0.1
**Position sizing is now conviction-based and aware of domain-specific market biases for more nuanced risk control.**
- Position sizing now uses conviction × domain bias, rather than fixed amounts or on-chain/GitHub signals.
- Integrated built-in domain_bias() multiplier: discounts for hype-driven categories (NFT/Metaverse, robots), boosts for lagged/underweighted areas (quantum, DeFi, synthetic bio).
- Added new risk tunables: YES/NO price thresholds, minimum trade size.
- Updated keyword list to clarify scope and simplify matching.
- Documentation now emphasizes the conviction logic and bias table, with updated code examples and risk tables.
v1.0.0
Emerging Tech Trader skill for Polymarket launches, providing advanced automated trading across niche emerging technology prediction markets.
- Trades on milestones in Web3/DeFi, NFT recovery, metaverse adoption, robotics, quantum computing, and synthetic biology.
- Utilizes both GitHub activity and on-chain data to identify unpriced technical progress.
- Built-in risk controls: configurable position sizes, spread, volume, and concurrency limits.
- Runs on a 15-minute schedule by default, but only paper trades until explicitly set to live mode.
- All strategy and risk parameters are tunable via environment variables and Simmer UI.
元数据
常见问题
Polymarket Emerging Tech Trader 是什么？
Trades Polymarket prediction markets on Web3/DeFi milestones, NFT market recovery, metaverse adoption, humanoid robotics deployments, quantum computing break... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 325 次。
如何安装 Polymarket Emerging Tech Trader？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install polymarket-emerging-tech-trader」即可一键安装，无需额外配置。
Polymarket Emerging Tech Trader 是免费的吗？
是的，Polymarket Emerging Tech Trader 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Polymarket Emerging Tech Trader 支持哪些平台？
Polymarket Emerging Tech Trader 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Polymarket Emerging Tech Trader？
由 diagnostikon（@diagnostikon）开发并维护，当前版本 v0.0.3。
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