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消息操作

用于ECC的以证据为先的实时消息工作流。当用户想要阅读短信或私信、恢复最近的一次性代码、在回复前检查会话线程,或证明实际检查了哪个消息来源时使用。

消息操作 是什么?

消息操作(Messages Ops)是一个专门用于处理实时消息检索任务的技能,它基于证据先行的原则,确保每一次消息操作都有明确来源可追溯。该技能适用于iMessage、私信、最近一次性代码的恢复、以及线程检查后回复等场景。它要求首先解析消息来源,包括本地消息、X/社交平台私信或其他基于浏览器的消息界面,然后进行精确的检索、检查或回复准备。对于一次性代码,建议优先搜索本地近期消息窗口,并在找到后立即停止;对于可能需要回复的线程,先阅读最新入站消息,识别未结束的循环,再交给正确的出站技能。最终输出必须包含使用的来源、线程或发送者、时间窗口以及明确的状态(已读、已找到代码、被阻止、等待回复草稿),从而提供完整、可审计的沟通记录。

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

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

消息操作 是做什么的?

当任务是实时消息检索时使用此技能:iMessage、私信、最近的一次性代码、或后续回复前的线程检查。

这不是邮件工作。如果主要操作界面是邮箱,请使用 email-ops。

技能栈

在相关情况下将这些ECC原生技能引入工作流:

  • email-ops — 当消息任务实际上是邮箱工作时
  • connections-optimizer — 当私信线程属于外部网络工作时
  • lead-intelligence — 当实时线程应指导目标定位或预热接触时
  • knowledge-ops — 当线程内容需要捕获到持久化上下文中时

使用时机

  • 用户说“读我的消息”、“检查短信”、“看看私信”或“找到验证码”
  • 任务依赖于实时线程或发送到本地消息界面的近期验证码
  • 用户希望证明哪个来源或线程被检查过

安全护栏

  • 首先解析来源:
    • 本地消息
    • X / 社交平台私信
    • 其他浏览器限制的消息界面
  • 不要在不指明来源的情况下声称已检查线程
  • 如果有现成的辅助方法或标准路径,不要即兴进行原始数据库访问
  • 如果身份验证或MFA阻止了界面,报告确切的阻止因素

工作流

1. 解析确切的线程

在执行任何事情之前,确定:

  • 消息界面
  • 发送者 / 接收者 / 服务
  • 时间窗口
  • 任务是检索、检查还是为回复做准备

2. 先读后写

如果任务可能变成后续的出站回复:

  • 读取最新的入站消息
  • 识别未结束的循环
  • 然后根据需要交给正确的出站技能

3. 将验证码视为聚焦检索任务

对于一次性验证码:

  • 先搜索本地近期消息窗口
  • 尽可能按服务或发送者缩小范围
  • 一旦找到验证码或聚焦搜索用尽则停止

4. 报告精确证据

返回:

  • 使用的来源
  • 线程或发送者(如可能)
  • 时间窗口
  • 确切状态:
    • 已读
    • 已找到验证码
    • 被阻止
    • 等待回复草稿

输出格式

来源
- 消息界面
- 发送者 / 线程 / 服务

结果
- 消息摘要或验证码
- 时间窗口

状态
- 已读 / 已找到验证码 / 被阻止 / 等待回复草稿

常见陷阱

  • 不要混淆邮箱工作和私信/短信工作
  • 不要在不指明来源的情况下声称已检索
  • 当任务是查找最近验证码时,不要在广泛搜索上浪费时间
  • 不要在不呈现阻止因素的情况下反复重试被阻止的身份验证路径

验证

  • 回复中指明消息来源
  • 回复中包含发送者、服务、线程或明确的阻止因素
  • 最终状态是明确且有限的

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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