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預測市場風險審查

在預測市場、交易組合、預言機及交易代理人工作流程中,審查合規性、安全性、資料品質、隱私及執行風險。在處理任何涉及場域驗證、用戶投資組合資料、API金鑰或交易規劃的工作流程前使用。

預測市場風險審查 是什麼?

此技能提供一個結構化的風險審查框架,專為涉及預測市場、交易籃子、預言機及交易代理人的工作流程設計。其主要目的是在觸及用戶財務上下文、場域驗證、投資組合資料或具執行能力的工具之前,識別並減輕潛在風險。審查涵蓋五個關鍵關卡:建議邊界(確保輸出僅為資訊性)、場域與監管邊界(驗證條款與限制)、資料品質(檢查流動性、到期價格及來源)、安全性(避免憑證暴露並強制執行最小權限存取)及隱私(最小化用戶資料使用)。最終輸出會提供審查範圍、通過/警告/失敗的發現、被阻擋的動作、所需的緩解措施以及安全的下一步行動。它支援任何強調安全性與合規性的AI代理平台,並確保在批准任何執行步驟之前,必須有獨立的人類審查與明確的用戶同意。

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

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

預測市場風險審查 是做什麼的?

在預測市場工作流程接觸用戶財務上下文、場域驗證、投資組合資料、自動化或具執行能力的工具之前,使用此技能。

審查關卡

建議邊界

  • 確認輸出為資訊性。
  • 移除買入/賣出/持有/規模的建議。
  • 保留明確的使用者手動決策點。

場域與監管邊界

  • 識別場域條款、地理限制、帳戶限制及 API 規則。
  • 在相關情況下,標記涉及賭博、衍生性金融商品、證券或商品的模糊性,以供法律審查。
  • 不得繞過場域限制或速率限制。

資料品質

  • 檢查市場流動性、價差、結算規則、過時價格及來源時間戳記。
  • 區分公開場域資料與 Itô 受控資料。
  • 若無標籤,不得混合公開與私人來源。

安全性

  • 不得請求或儲存私鑰、助記詞或密碼。
  • 將 ITO_API_KEY 及場域 API 金鑰排除在日誌與文件之外。
  • 預設使用唯讀範圍。
  • 在私有的執行功能新增前,要求設置斷路器、支出限制、預演及人類核准。

隱私

  • 盡量減少用戶投資組合、財務及知識庫資料。
  • 在公開成品中編輯私人來源。
  • 僅保留審查所需的欄位。

輸出合約

回傳:

  1. 審查範圍
  2. 通過/警告/失敗的發現
  3. 被阻擋的動作
  4. 所需的緩解措施
  5. 安全的下一步

若有任何具執行能力的步驟被請求,則需要一份獨立的實作計畫及明確的使用者核准。

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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