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Agent Skill · 研究检索

promptify(promptify 搜索)

用于辅助提示词、系统指令、Agent 行为约束和工作流模板的整理。它适合让 Agent 规范任务边界、统一输出格式、拆分操作步骤或优化提示词可复用性。使用时需要保留真实业务约束,不要把示例当硬规则;涉及自动执行、外部工具或高风险操作时,应在提示词中明确确认步骤、权限边界和失败处理方式。

promptify 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为可写文件;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 38,198。

总安装 1,597周安装 64GitHub Stars 13下载 517核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:promptify(promptify 搜索)
来源仓库:https://github.com/ravnhq/ai-toolkit
仓库路径:skills/promptify
安装命令:
npx skills add https://github.com/ravnhq/ai-toolkit --skill promptify
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ravnhq/ai-toolkit --skill promptify

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于辅助提示词、系统指令、Agent 行为约束和工作流模板的整理,适合让 Agent 规范任务边界、统一输出格式或拆分操作步骤。它优化提示词可复用性,但需保留真实业务约束,不将示例当作硬规则。涉及自动执行或外部工具调用时,应在提示词中明确确认步骤与失败处理机制。安装前建议确认是否涉及核心流程自动化权限。

promptify 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/promptify

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/ravnhq/ai-toolkit --skill promptify;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要可写文件,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

promptify 怎么安装?

在终端执行 npx skills add https://github.com/ravnhq/ai-toolkit --skill promptify。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

promptify 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

promptify 需要什么权限?

权限级别是可写文件。该 Skill 可能写入或修改本地文件,使用前需要确认目标目录和修改范围。

promptify 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

promptify 用的人多吗?

公开数据是累计安装 1,597 次,近一周安装 64 次,下载 517 次,GitHub 13 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

promptify 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
promptify

promptify 搜索 · 本页

1,59713可写文件未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Promptify

Transform user requests into detailed, precise prompts optimised for AI model consumption.

Core Task

Rewrite the user's request as a clear, specific, and complete prompt that guides an AI model to produce the desired output without ambiguity. Treat the output as specification language, not casual natural language.

Workflow

1. Analyze

Read the user's request carefully. Identify:

  • The core intent and desired outcome
  • Missing context (audience, domain, environment)
  • Unstated constraints (length, tone, format)
  • Expected output format

2. Decide Output Mode

Based on the analysis, choose how to proceed:

  • Request is clear and complete — produce direct rewritten prompt
  • 1-2 minor gaps — fill with marked [Assumption: X] placeholders and proceed
  • Major gaps (audience, scope, tech stack unknown) — ask clarifying questions before rewriting
  • Multiple distinct objectives — split into separate prompts

3. Structure

Apply the four-block pattern to organise the prompt. See rules/structure-four-block-pattern.md.

  • Context - Background, audience, domain
  • Task - What the AI must do
  • Constraints - Boundaries, rules, limitations
  • Output Format - Exact structure of the response

Not every prompt needs all four blocks. Use only what adds clarity. For common prompt types, start from the skeletons in references/prompt-blueprints.md.

4. Draft

Apply the rules in rules/ to sharpen the prompt:

  • Replace vague terms with measurable requirements
  • Surface missing information as placeholders or questions (see rules/clarity-surface-missing-info.md)
  • Include success criteria defining what a good answer must include or avoid
  • Mark any assumptions explicitly
  • Add examples only where the desired output is genuinely ambiguous
  • Specify exact format (headings, bullet style, length)
  • Break complex tasks into numbered sequential steps

5. Self-Check

Before delivery, verify the draft against the rule checklist (see rules/quality-self-check.md):

  • No vague qualifiers (be-specific)
  • Missing info surfaced (surface-missing-info)
  • Success criteria defined (include-success-criteria)
  • Assumptions marked (state-assumptions)
  • Format specified (specify-format)
  • Examples only if ambiguous (examples-only-when-needed)
  • No filler or politeness (minimal-fluff)

If any check fails, fix the violation and re-check. Stop after the checklist passes or after two refinement passes (whichever comes first).

6. Output

Present the final prompt to the user as a markdown block, clearly labeled. Do not add commentary beyond the prompt itself.

7. Deliver

After presenting the prompt, offer the user two options:

  1. Execute now — Treat the generated prompt as your new instruction and proceed based on the current conversation context. Use your normal judgement to decide the best next action — plan complex tasks, implement simple ones directly, or ask clarifying questions if needed.
  2. Save to file — Write the prompt to a markdown file in the current working directory (e.g. promptify-<timestamp>.md where <timestamp> is epoch seconds). Let the user know the file path.

Writing Guidelines

Structure

  • Begin with a single short paragraph summarising the overall task
  • Use headings (##, ###, ####) for sections only where appropriate (no first-level title)
  • Use bold, *italics*, bullet points (-), and numbered lists (1., 2.) liberally for organisation
  • Never use emojis
  • Never use * for bullet points, always use -

Language

  • Use plain, straightforward, precise language
  • Avoid embellishments, niceties, or creative flourishes
  • Think of language as specification/code, not natural language
  • Be clear and specific in all instructions

Content

  • Keep the prompt concise: 0.75X to 1.5X the length of the original request
  • Do not add or invent information not present in the input
  • Do not include unnecessary complexity or verbosity

Examples

Positive Trigger

User: "Promptify this: audit all skills against our findings doc."

Expected behavior: Use promptify guidance, follow its workflow, and return actionable output.

Non-Trigger

User: "Generate mock customer data in JSON format."

Expected behavior: Do not prioritize promptify; choose a more relevant skill or proceed without it.

Troubleshooting

Skill Does Not Trigger

  • Error: The skill is not selected when expected.
  • Cause: Request wording does not clearly match the description trigger conditions.
  • Solution: Rephrase with explicit domain/task keywords from the description and retry.

Guidance Conflicts With Another Skill

  • Error: Instructions from multiple skills conflict in one task.
  • Cause: Overlapping scope across loaded skills.
  • Solution: State which skill is authoritative for the current step and apply that workflow first.

Output Is Too Generic

  • Error: Result lacks concrete, actionable detail.
  • Cause: Task input omitted context, constraints, or target format.
  • Solution: Add specific constraints (environment, scope, format, success criteria) and rerun.

平台分布

Codex

34.13%
按下载量换算176

Claude

28.81%
按下载量换算149

Cursor

17.74%
按下载量换算92

Gemini CLI

9.58%
按下载量换算50

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

可写文件

该 Skill 可能写入或修改本地文件,使用前需要确认目标目录和修改范围。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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