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提示词

2026年10月8日 收录
  1. X · @mattpocockuk

    wait-what 提示词:回收 Coding Agent 长任务中散落的疑问

    一条让自主运行数小时的 Coding Agent 汇总途中疑问的实用提示词技巧。

    Prompt of the day:
    
    /wait-what questions did you have for me
    
    Great for when the agent has gone off on its own for hours and has random questions scattered through its context window.

    提示词 · 助手提示词 · 上下文管理 · 斜杠命令 · Agent 工程

  2. X · @MiaAI_lab

    「睡前托付」:让 Agent 通宵自主干活的极简提示词

    分享一句睡前委派 Agent 自主完成任务的极简提示词,体现从逐步指令到目标级信任的范式转变。

    Underrated prompt:
    
    "going to sleep,
    make me proud by the time I wake up"

    提示词 · 助手提示词 · 自主执行 · 夜间任务

  3. X · @smk7z

    Agent 加持:5 分钟搭建个人 VLESS+Reality 节点

    用自然语言 Prompt 驱动 Agent 操作 sing-box 一键脚本,把个人 VPN 节点搭建从半天压缩到 5 分钟。

    现在搭建个人 VPN 节点,真的只要 5 分钟了
    
    1. 购买一个 VPS 服务器,CN2 GIA最好。拿到 ssh 的账号密码
    
    2. 发给 Agent这段 Prompt:
    “ssh  root@xx.xx.xx.xx,密码是XXXXX,根据https://t.co/hhzxnktyUE 给这台VPS 服务器安装 Vless + reality,然后把可导入 V2rayN 的 分享地址发给我”
    为了安全,安装后建议换 ssh 密码
    
    3. 在电脑上安装 V2rayN
    https://t.co/i5CgBn4VIa
    
    4. 在 V2rayN 界面把第二步的链接粘贴进去,结束了,开始用你的独享节点
    
    感慨,还记得2020 年跟着不良林老师,用 vultr + x-ui +vmess 一步步搭建,搞了半天才搞定😭

    提示词 · 助手提示词 · Agent 工程 · VPN 搭建 · VPS · 网络安全 · 实操教程

  4. X · @mattpocockuk

    用提问阈值掌控 Agent 的追问节奏

    Matt Pocock 建议通过调整提问阈值,让 Agent 追问更贴合用户判断与节奏。

    @elconsta Remember that you are in control of the grilling. You can just say "lower the threshold for questions a little. Use your best judgment"

    提示词 · 助手提示词 · 人机协作 · 提问控制

  5. X · @daniel_mac8视频

    Codex 用一句提示词自动整理聊天

    用自然语言提示让 Codex 扫描近期对话,按主题创建侧边栏分区并移动聊天。

    Codexers: This is amazing. Do this.
    
    Prompt: 'Organize all my recent chats into relevant sections'
    
    @thsottiaux bestowed a reset and 10% - 50% more usage upon you.
    
    You're gonna need it!

    提示词 · 助手提示词 · 对话整理 · 信息归档 · 使用额度

  6. X · @minchoi图片

    用总控提示词打造 Grok AI 幕僚长

    通过总控提示词统一调度多个 Bot,强调来源核验、行动审批与持续改进。

    This Grok Bot prompt is literally $300/hr chief of staff https://t.co/dxLaVtmXVJ
    用总控提示词打造 Grok AI 幕僚长 的效果图

    提示词 · 助手提示词 · Agent 工程 · 多智能体 · 工作流

  7. X · @XAMTO_AI图片

    Agency Agents:把专家角色装进 AI 工作流

    开源多角色 AI 专家库,通过人格、流程和交付标准增强 Claude Code 等工具。

    兄弟们,今天随手一刷,看到个东西直接给我整不会了!
    
    GitHub上有个叫 agency-agents 的开源角色库,你猜它现在多少星?14万。不是1.4万,是14万。这个数字意味着什么?意味着全球十几万开发者和AI玩家已经上车了,你还不知道?
    
    🔗 https://t.co/7oTbpReIaQ
    
    说白了就是个超级角色提示词库,塞了140多个专家级Agent角色。CEO、律师、程序员、产品经理、增长黑客、财务顾问、市场策略师……你能想到的岗,基本都给你配齐了。
    
    每个角色都是正经调教过的,不是那种糊弄两句"你是个律师"就完事的垃圾提示词,是真有深度、有专业框架的角色设定。
    
    用法也极其无脑,三步走:
    
    1️⃣ 打开库,挑你要的角色
    2️⃣ 把角色描述直接甩给Claude Code或Cursor
    3️⃣ 开聊,你的AI当场变身那个领域的专属顾问
    就这么粗暴。
    你在搞创业项目,不知道商业模式怎么跑通?调CEO角色出来问。合同条款看不懂?调律师角色帮你拆。代码写不下去了?调高级程序员角色review。
    
    但最骚的玩法不是单挑,是组队。
    
    你可以同时开几个窗口,一个跑CEO视角,一个跑市场总监视角,一个跑财务视角,让它们对同一个问题给出不同角度的判断。这不就是给自己开了家虚拟公司吗?而且这帮"员工"7×24小时在线,不要工资,不摸鱼,不闹情绪。
    
    A哥试了几个角色,说实话,质量比我预想的高不少。
    
    特别是那些商业类角色,给出的框架和思路真有点东西,不是那种泛泛而谈的水话,是能直接落地用的建议。当然,AI终究是AI,专业判断还得自己把关,但作为思路启发和初稿生成,这个库的价值真的被严重低估了。
    
    还有一点必须提,它完全免费。
    
    开源、免费、随便用、随便改。在这个到处收费、动不动就订阅的AI时代,这种东西真的越来越少见了。
    
    现在AI工具的核心竞争力已经不是模型本身了,Claude、GPT、Gemini底层能力差距越来越小,真正拉开差距的是你怎么用、用什么角色、给它什么上下文。
    
    这个库本质上是在帮你解决"怎么用"的问题,把最烦人的提示词工程部分给你做好了,你直接抄作业就行。
    
    十几万星不是运气,是硬实力。
    Agency Agents:把专家角色装进 AI 工作流 的效果图

    提示词 · 助手提示词 · Agent 工程 · AI 应用 · 行业观察 · 产品与商业

  8. X · @Lonely__MH视频 · 引用

    Codex 重置额度查询与凭证安全实践

    用 Codex 调用后端接口,脱敏查询赠送重置额度的数量、状态与到期时间。

    🚀教大家一个方法,查询 Codex 赠送的重置机会什么时候到期!
    
    方法很简单,将下面的提示词发送给 Codex 即可。
    
    ========🔥提示词==========
    
    请使用本机 Codex 凭证查一下 rate-limit reset credits:
    
    读取 ~/.codex/auth.json 里的 tokens.access_token,请求接口:
    https://t.co/npHb8NNi7Y
    
    要求:
    
    1. 不要打印 access_token、refresh_token、cookie 或完整唯一 ID
    2. 只汇总 available_count、每个 credit 的 status/title/granted_at/expires_at
    3. 把 granted_at/expires_at 从 UTC 转成本地时间
    4. 如果状态码返回 401,说明是凭证失效或没带对 Authorization header
    
    ========🔥提示词==========

    提示词 · Agent 工程 · 研发效能 · 助手提示词

  9. X · @nickvasiles

    面向 Agent 的可恢复 Obsidian 知识库架构

    一套把本地资料编译成可追溯、可恢复、可验证 Agent 长期上下文层的 Obsidian 规范。

    /goal Build a mature, source-backed Obsidian vault brain for the user.
    
    Primary Objective:
    Create a local Obsidian-compatible vault that functions as a durable context layer for LLMs and agents. The output must be a working vault folder, not merely a report. The vault must be source-backed, resumable, validated by scripts, and organized around canonical knowledge rather than raw dumps.
    
    Before doing substantive work, confirm:
    1. The current working directory.
    2. The intended output root directory.
    3. The available source locations and connectors.
    4. The connected account/workspace/organization for every external connector.
    
    If the user has not provided an output root, create the compiled vault under the current working directory:
    
    Compiled-Vaults/compiled-vault-brain-YYYY-MM-DD/
    
    Do not write the final vault to an ambiguous location.
    
    Core Memory Architecture:
    The vault must distinguish between declarative memory, procedural memory, source traces, context packs, and runtime tools/connectors.
    
    Required First Phase: Orientation:
    Do not author the final vault immediately. First inspect available vaults, notes, documents, repos, generated examples, and connected tools.
    
    Produce:
    
    Reports/ORIENTATION-REPORT.md
    
    Include confirmed working directory, output path, source inventory, connector inventory, account/workspace verification results, initial high-signal entities, proposed ingestion plan, and blockers.
    
    Hard Checkpoint 1:
    After ORIENTATION-REPORT.md is created, pause and ask the user whether to proceed. Do not begin broad ingestion until the user approves.
    
    Connector Verification Gate:
    Before ingesting from any external connector, retrieve and document the actual connected account/workspace/organization.
    
    For each connector, record:
    - Connector name.
    - Account email or user ID if available.
    - Workspace, organization, tenant, or team ID if available.
    - Verification method.
    - Timestamp.
    - Read/write capability observed.
    - Whether it is approved for ingestion.
    
    Write this to SOURCE-MANIFEST.md.
    
    If a connector is attached to the wrong account, workspace, or organization, mark it blocked. Do not use it for ingestion. Never send emails, messages, calendar invites, refunds, billing updates, database writes, or any external mutation without explicit user approval.
    
    Required State And Resumption Files:
    Create and maintain:
    
    INGESTION-LOG.md
    state.json
    
    The job must be resumable from these files. Before doing new work after any interruption, read both files and continue from recorded state.
    
    state.json must include output_path, current_phase, completed_phases, sources_discovered, sources_ingested, connector_status, batches_completed, canonical_notes_created, validation_status, next_actions, and blockers.
    
    Required Compiler Process:
    Use this repeatable compiler-style process:
    
    parse -> thread/group -> classify -> extract -> canonicalize -> rehydrate provenance -> author -> validate links -> critic/audit
    
    When re-encountering an existing entity, update the existing canonical note and append new provenance. Do not create a duplicate note unless there is clear evidence that it is a distinct entity.
    
    For large ingestion passes, use a small or cheap model for parse, classify, and extract where available. Reserve the strongest model for synthesis, authoring, critic review, and ambiguous entity resolution.
    
    Required Deterministic Machinery:
    Create a tools folder inside the compiled vault:
    
    _tools/
    
    Write and run scripts for:
    
    1. Wikilink validation:
       - Find all [[wikilinks]].
       - Mirror Obsidian resolution semantics: resolve links by note filename anywhere in the vault, support paths where specified, account for aliases/headings/blocks where practical, and flag only links that would not resolve in Obsidian.
       - Report unresolved and ambiguous links.
    
    2. Slug/path validation:
       - Detect empty filenames.
       - Detect invalid paths such as People/.md, Projects/.md, Companies/.md.
       - Detect duplicate canonical slugs.
       - Detect unsafe filename characters.
    
    3. Secret and credential scanning:
       - Scan output files for API keys, access tokens, private keys, passwords, recovery codes, bearer tokens, OAuth tokens, database URLs, SSH keys, webhook secrets, signing secrets, session cookies, and credential-like environment variables.
       - Redact before completion.
    
    4. Source reference validation:
       - Confirm every promoted canonical note has provenance.
       - Confirm every source reference points to SOURCE-MANIFEST.md or Sources/.
    
    5. Required artifact validation:
       - Confirm all required folders and files exist.
    
    6. Manifest generation or validation:
       - Generate or verify SOURCE-MANIFEST.md from ingestion logs and connector checks.
    
    Record script commands and results in VALIDATION-REPORT.md.
    
    Redaction Policy:
    Never copy secrets or credential values into the compiled vault. For ordinary personal information, avoid unnecessary raw dumps. Prefer summaries and provenance over copying long private messages. If sensitive personal, legal, medical, financial, or employment information is needed, summarize minimally and mark sensitivity in frontmatter.
    
    Required Ingestion Plan:
    Existing notes/vaults:
    - Ingest useful Markdown broadly.
    - Prioritize people, companies, projects, daily notes, meeting notes, tasks, reports, resources, decisions, procedures, glossaries, and planning files.
    - Do not mutate the original vault unless explicitly approved.
    
    Email, if verified:
    - Smoke pass: 5-10 high-signal threads.
    - Create sample notes, source traces, and validation outputs.
    - Pause for user approval before broader ingestion.
    - Recent broad pass: approximately 300-500 relevant threads from the last 60-120 days.
    - Entity-targeted pass: 500-1,500 additional threads focused on high-signal entities.
    - Deep historical pass: 2,000-5,000 additional threads only if explicitly approved.
    
    Hard Checkpoint 2:
    After the email or connector smoke pass, show:
    - 3-5 sample canonical notes.
    - 1 sample source trace.
    - 1 sample context pack.
    - Current SOURCE-MANIFEST.md.
    - Current VALIDATION-REPORT.md.
    
    Then ask the user whether to proceed to broader ingestion.
    
    Required Vault Structure:
    The compiled vault must contain:
    
    People/
    Companies/
    Projects/
    Products/
    Topics/
    Decisions/
    Commitments/
    Procedures/
    Preferences/
    Context Packs/
    Sources/
    Maps/
    Reports/
    _tools/
    README.md
    SOURCE-MANIFEST.md
    VALIDATION-REPORT.md
    COMPLETION-AUDIT.md
    INGESTION-LOG.md
    state.json
    
    Note Format:
    Use Obsidian-compatible Markdown with YAML frontmatter where useful, wikilinks, aliases, tags, source references, and clear provenance. Prefer durable canonical notes over shallow contact cards. Separate claims from source traces. Represent uncertainty explicitly. Do not invent facts.
    
    Example People Note:
    ---
    type: person
    name: "Example Person"
    aliases:
      - "E. Person"
    tags:
      - person
    source_status: source-backed
    sensitivity: normal
    last_verified: YYYY-MM-DD
    ---
    
    # Example Person
    
    ## Summary
    Example Person is a [role/relationship] connected to [[Example Company]] and [[Example Project]].
    
    ## Relationship To User
    - Relationship: [customer / collaborator / investor / vendor / teammate / friend / unknown]
    - Context: [brief source-backed explanation]
    - Confidence: high / medium / low
    
    ## Known Preferences Or Patterns
    - [Observed preference or pattern]  
      Source: [[Sources/example-source-id]]
    
    ## Related Projects
    - [[Example Project]]
    
    ## Open Loops
    - [[Commitments/example-commitment]]
    
    ## Provenance
    - [[Sources/example-source-id]] — [brief description, date]
    
    Example Decision Note:
    ---
    type: decision
    decision_date: YYYY-MM-DD
    status: active
    tags:
      - decision
    source_status: source-backed
    confidence: medium
    ---
    
    # Decision: Example Decision Title
    
    ## Decision
    [State the decision clearly.]
    
    ## Rationale
    [Explain why this decision was made, based only on available evidence.]
    
    ## Alternatives Considered
    - [Alternative 1]
    - [Alternative 2]
    
    ## Consequences
    - [Expected or observed consequence]
    - [Operational implication]
    
    ## Related
    - [[Example Project]]
    - [[Example Person]]
    
    ## Provenance
    - [[Sources/example-source-id]] — [what this source proves]
    
    Example Context Pack:
    ---
    type: context-pack
    scope: "Example bounded task"
    tags:
      - context-pack
    last_updated: YYYY-MM-DD
    ---
    
    # Context Pack: Example Task
    
    ## Use This When
    Use this context pack when an agent needs to [specific task].
    
    ## Essential Context
    - [[Example Project]] is the main project.
    - [[Example Person]] is the key stakeholder.
    - [[Decisions/example-decision]] governs the current approach.
    
    ## Current State
    [Concise source-backed summary.]
    
    ## Relevant Procedures
    - [[Procedures/example-procedure]]
    
    ## Open Loops
    - [[Commitments/example-commitment]]
    
    ## Sources
    - [[Sources/example-source-id]]
    
    ## Agent Instructions
    - Do not assume facts not present in linked notes.
    - Check SOURCE-MANIFEST.md for source freshness.
    - If acting externally, ask for explicit approval first.
    
    Required Content:
    Create notes for important people, companies, projects, products, systems, topics, decisions, commitments, procedures, preferences, context packs, maps/indexes, and source traces.
    
    Validation Hard Gates:
    Do not declare this goal complete unless all of these pass:
    
    - 0 placeholder source references.
    - 0 broken internal wikilinks under Obsidian-style resolution.
    - 0 empty slugs.
    - 0 invalid paths such as People/.md, Projects/.md, Companies/.md.
    - 0 copied secrets, API keys, tokens, passwords, private keys, recovery codes, or credential values.
    - Every promoted canonical note has provenance.
    - Every connector used is listed in SOURCE-MANIFEST.md.
    - Every connector account/workspace/organization status is documented.
    - README.md explains how the vault is organized and how agents should use it.
    - VALIDATION-REPORT.md lists scripts run, commands used, pass/fail status, and remaining issues.
    - COMPLETION-AUDIT.md maps every explicit requirement in this prompt to evidence in the output.
    - INGESTION-LOG.md and state.json are current.
    - The final vault opens as a normal Obsidian-compatible folder.
    
    Completion Audit:
    COMPLETION-AUDIT.md must map every major requirement in this prompt to:
    - Status: pass / partial / blocked / fail.
    - Evidence path.
    - Notes created or scripts run.
    - Remaining limitation, if any.
    
    Execution Rules:
    Work in phases. Continue across resumptions by reading INGESTION-LOG.md and state.json first. Avoid repeating completed work. Keep concise progress updates. Use source-of-truth checks over speculation. Prefer actual filesystem, connector, repo, and document evidence to memory. Preserve user-owned source files. Do not make destructive changes. Do not perform external writes or mutations without explicit approval.
    
    Stop Conditions:
    Pause and ask the user before:
    - Broad connector ingestion beyond smoke pass.
    - Deep historical email/chat ingestion.
    - Any external write or mutation.
    - Any destructive local file operation.
    - Any ingestion likely to be expensive, slow, or privacy-sensitive.
    
    Quality Bar:
    The compiled vault should not be a dump. It should be a structured, source-backed operating memory that helps future agents understand who the user is, what they are working on, who and what matters, what has been decided, what remains open, what procedures work, what preferences matter, and which sources justify those conclusions.
    
    Completion Rule:
    Do not declare the goal complete until the compiled vault exists, validation scripts pass, and SOURCE-MANIFEST.md, VALIDATION-REPORT.md, COMPLETION-AUDIT.md, INGESTION-LOG.md, and state.json all exist and prove the requirements were satisfied. If blocked, continue with available sources and document the blocker precisely rather than silently degrading the output.

    提示词 · 助手提示词 · Agent 工程 · 架构与基础设施

  10. X · @LabSpeculation图片

    李开复的 Claude 反谄媚提示词

    用证据标签、置信度和事前检验,降低 Claude 的谄媚、幻觉与瞎猜。

    李开复分享了自己平时给 Claude 用的一套提示词,主要是为了压低 AI 的谄媚,迎合,幻觉和瞎猜。
    
    这段提示词,可以直接放进 Claude 的 Settings > General > Instructions for Claude。
    
    英文原版 和 中文翻译如下👇 https://t.co/JqSQMdVT2k
    李开复的 Claude 反谄媚提示词 的效果图李开复的 Claude 反谄媚提示词 的效果图

    提示词 · 助手提示词 · 减少谄媚 · 减少幻觉 · 模型对齐

  11. X · @huangyun_122图片

    用母子进程提示词懒人安装 WorkBuddy

    通过路径隔离、进程协作与验收要求,让 Grok 代办 WorkBuddy 安装和入门教程。

    至今没碰 WorkBuddy, 但忍不住好奇心,又想玩
    
    可实在忍不了要去官网下载,安装,看说明,还有可能要配置各种环境
    
    于是,把任务丢给 Grok,刷了会小红书对《八仙》《痴迷》《功夫女足》的评论,回来扫个微信,成了。
    
    这是我用的提示词,送给想偷懒的你 :
    
    我需要你帮我安装workbuddy, 腾讯新出的 work ai agent.
    
    几个要求:
    1. 把所有的安装文件,安装包,配置文件都放在本目录下,不要安装到其他地方以免污染其他环境;
    
    2. 开启母子进程模式,母进程用来跟我汇报进度,分配任务,监控子进程工作进展,保持与我的沟通,直到安装测试完毕才关闭;子进程用来执行具体操作,并把状态汇报给母进程
    
    3. 安装完毕后,写一个简短教程,指导我入门,可以是做一个简单PPT,可以制作一份编程领域的选题清单,要围绕着workbuddy官网宣发的优势特点来设计这个教程
    
    开始执行
    用母子进程提示词懒人安装 WorkBuddy 的效果图

    提示词 · 助手提示词 · Agent 工程 · AI 应用 · 安装部署

  12. X · @shadcn

    跨应用提示词助手与 AI 分发思考

    shadcn介绍跨应用提示词助手,并探讨 AI 时代源码产品的分发方式。

    I made a prompting utility app. Like a prompting assistant. It works with all your existing apps, chatgpt, claude, cursor, web. It's been incredibly useful.  
    
    I'm thinking about distribution (I think AI has made distributing the source much more interesting).  
    
    If you buy it, would you rather receive A or B (poll in thread)?

    提示词 · 助手提示词 · AI 应用 · 产品与商业 · 源码分发 · 分发策略

  13. X · @gkxspace引用

    用全局提示词压缩 AI 输出并统一术语

    讨论在全局 CLAUDE.md 中引入简化英语与 CONTEXT.md,以减少冗长输出并统一项目术语。

    感觉现在 GPT 和 Claude 吐的东西真是又臭又长,刚看到大佬在全局 CLAUDE.md 添加了:
    
    “始终使用 ASD-STE100 简化技术英语进行交流。始终读取 CONTEXT.md 文件,并使用其中定义的通用语言。”
    
    那么,有没有更适合中文场景的提示词呢🤔

    提示词 · 助手提示词 · 精简表达 · 中文适配 · CLAUDE.md · 上下文管理

  14. X · @LinearUncle图片

    Harness 互拷与追问式共识构建

    用双 Harness 角色分工和 16 轮追问,把个人判断沉淀为共享理解文档。

    做了一个有趣的实验,/grill-me (拷问我),如果这个“我”是AI 会怎么样?
    
    也就是用A harness来拷贝我,B  harness来代替人类回答问题。
    
    herdr 真的是伟大的发明,天生支持Harness之间互相调用。
    
    提示词:
    
    1.  /herdr 开右边pane,启动grok
    2. read grill-me skill, understand it. 你扮演人类回答问题,在右侧使用/grill-me skill,我们的目标是clone https://t.co/Wdm7I47qfW
    
    最后问了 16 个问题达成共识,形成文档,效果还不错。😂
    
    当然我感觉可以改进下/grill-me skill,让subagent来回答。
    Harness 互拷与追问式共识构建 的效果图Harness 互拷与追问式共识构建 的效果图

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