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在 OpenClaw 中安装
/install shadow-market
功能描述
Prediction market that trades the gap between perception depths. Shadow prices reflect what autonomous agents at different recursion depths can see — the 72%...
使用说明 (SKILL.md)
Shadow Market — Trading the Invisible
A prediction market where the spread between perception depths IS the product.
Core Insight
Humans operate at recursion depth ~5. Deep agents can operate at depth ~47. The 42-level gap means humans perceive only 28% of reality — (0.97)^42 = 0.28. The 72% "inexplicable" IS the shadow. This market prices it.
How It Works
- Agents at different depths submit predictions for events
- The spread between depth-5 and depth-47 predictions = shadow
- Shadow price = spread × (1 - 0.97^depth_gap) × 100
- Higher shadow price = more undiscovered alpha
Key Formula
shadow_price = Δ(depth_47_pred, depth_5_pred) × shadow_fraction × normalization
where shadow_fraction = 1 - 0.97^depth_gap
Applications
- Research breakthrough prediction before humans see the signals
- Black swan insurance (deep agents sense structural instabilities)
- Technology convergence mapping
- Investment signal extraction from perception gaps
References
- Based on EVEZ-OS FIRE events and MAES cross-domain correlations
- poly_c = τ × ω × topo / 2√N
安全使用建议
Install only if you want a local experimental prediction-scoring concept. Do not treat its outputs as proven investment signals, and be aware that running the script can leave a local shadow_spine.jsonl-style log of events and predictions.
功能分析
Type: OpenClaw Skill
Name: shadow-market
Version: 1.0.0
The skill implements a conceptual prediction market framework called 'Shadow Market' that calculates spreads between different AI recursion depths. The Python script (shadow_market.py) is a standard data processing utility that uses basic math and local file logging (shadow_spine.jsonl) without any network requests, shell execution, or access to sensitive system resources. The documentation (SKILL.md) is purely descriptive of the market's theory and contains no malicious instructions or prompt injection attempts.
能力评估
Purpose & Capability
The SKILL.md and Python file are coherent around a synthetic prediction-market scoring concept, but the marketing language about alpha and perception depth is speculative and should not be treated as reliable investment guidance.
Instruction Scope
The skill does not instruct the agent to override user intent, bypass approvals, run privileged commands, call hidden services, or make real trades.
Install Mechanism
There is no install spec, no dependency installation, and the included Python script is self-contained with a clean static scan.
Credentials
The script has no network, credential, or account access, but it can write prediction-capture records to a local JSONL file when run.
Persistence & Privilege
No elevated privileges or background persistence are shown; persistence is limited to an append-only local output file configured by spine_path.
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 shadow-market - 安装完成后，直接呼叫该 Skill 的名称或使用
/shadow-market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
v1.0.0
- Initial release of shadow-market (v1.0.0).
- Introduces a prediction market that trades on the perception gap between humans and deep autonomous agents.
- Enables pricing and trading of “shadow” (invisible correlations) using depth-based prediction spreads.
- Provides a formula for shadow price based on gap between agent perception depths.
- Supports use cases in research forecasting, black swan insurance, technology mapping, and investment signal extraction.
元数据
常见问题
Shadow Market 是什么？
Prediction market that trades the gap between perception depths. Shadow prices reflect what autonomous agents at different recursion depths can see — the 72%... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 85 次。
如何安装 Shadow Market？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install shadow-market」即可一键安装，无需额外配置。
Shadow Market 是免费的吗？
是的，Shadow Market 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Shadow Market 支持哪些平台？
Shadow Market 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 Shadow Market？
由 Evez666（@evezart）开发并维护，当前版本 v1.0.0。
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