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预测市场风险审核

在预测市场工作流处理场所认证、用户投资组合数据、API密钥或交易计划之前,用于审核合规性、安全性、数据质量、隐私和执行风险。

预测市场风险审核 是什么?

此技能专为AI代理设计,用于在预测市场工作流接触用户财务数据、场所认证、交易自动化或执行工具之前进行全面的风险审核。它通过五个关键审查门(建议边界、场所与监管边界、数据质量、安全性、隐私)确保工作流合规且安全。输出内容包括审核范围、通过/警告/失败发现、被阻止的操作、必要缓解措施及安全下一步,明确禁止执行步骤直至获得用户批准。该技能适用于任何处理预测市场、篮子、预言机或交易代理工作流的AI代理(如Claude Code、Cursor、Codex),并强制要求使用只读范围、断路器、支出限制和人工审批。

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/prediction-market-risk-review

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

预测市场风险审核 是做什么的?

在预测市场工作流触及用户财务上下文、场所认证、投资组合数据、自动化或执行能力工具之前,请使用此技能。

审核门

建议边界

  • 确认输出为信息性内容。
  • 移除买入/卖出/持有/规模建议。
  • 保持手动用户决策点明确。

场所与监管边界

  • 识别场所条款、地理限制、账户限制及API规则。
  • 在必要时标记博彩、衍生品、证券或大宗商品的歧义性以进行法律审核。
  • 不得绕过场所限制或速率限制。

数据质量

  • 检查市场流动性、价差、解析规则、过时价格及来源时间戳。
  • 将公共场所数据与 Itô 门控数据分离。
  • 不得混合公共与私有来源而不加标签。

安全性

  • 不得请求或存储私钥、种子短语或密码。
  • 将 ITO_API_KEY 和场所 API 密钥排除在日志和文档之外。
  • 默认使用只读范围。
  • 在私有实现添加执行之前,要求使用断路器、支出限制、试运行和人工批准。

隐私

  • 最小化用户投资组合、财务和知识库数据。
  • 在公开制品中编辑私有来源。
  • 仅保留审核所需的字段。

输出合约

返回:

  1. 审核范围
  2. 通过/警告/失败发现
  3. 被阻止的操作
  4. 必要缓解措施
  5. 安全下一步

如果请求了任何可执行的步骤,则要求单独的实施计划和明确用户批准。

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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