ai-transcript-action-extractor

SKILL效率
效率 未标注权限 许可证不明确
安装这个技能

Convert pasted, user-provided transcripts or chat exports into a structured action register with tasks, owners, dates, decisions, risks, open questions, and verification checks.

一句话选型结论

按资料字段整理

ai-transcript-action-extractor是效率类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类效率 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_15292d5a/yjkj-ai-transcript-action-extractor
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

效率
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_15292d5a仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791721175
正文体量7.3 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
整理待办与日程

把零散任务收进清单,排出优先级。

批量处理重复任务

把固定动作做成模板,重复执行。

把流程写成清单

把口头流程整理成可复用的步骤。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在效率场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
ai-transcript-action-extractor当前 未标注权限 未标注 未标注 未标注 有
Nano PDF 文档 联网访问 ClawHub 市场 424.9 万 OpenClaw 有
自动更新程序 浏览器控制 ClawHub 市场 296.4 万 OpenClaw 有
Gemini 助手 联网访问 ClawHub 市场 254.7 万 OpenClaw 有
word DOCX 文档 联网访问 ClawHub 市场 239.6 万 OpenClaw 有
Excel XLSX 前端 联网访问 ClawHub 市场 227.0 万 OpenClaw 有

SKILL.md 全文

7.3 KB
模型实际读到的说明书原文,来自技能仓库

AI Transcript Action Extractor

Overview

AI Transcript Action Extractor helps a user turn a pasted transcript, chat export, meeting notes dump, interview excerpt, support conversation, or long discussion thread into a clean action register. It focuses on extracting work items, owners, dates, decisions, risks, dependencies, open questions, and follow-up checks from text the user provides.

This skill is prompt-only and document-only. It does not retrieve transcripts, join meetings, access recordings, browse private workspaces, call APIs, use hidden context, or send messages. Work only from pasted or user-provided text.

When to Use

Use this skill when the user asks for help with:

  • Extracting action items from a long transcript or chat log
  • Turning meeting text into tasks, owners, due dates, and decisions
  • Cleaning a raw AI transcript into a structured action table
  • Finding unresolved questions, risks, dependencies, and follow-ups
  • Creating a prompt-and-review workflow for an external AI tool using redacted text

Trigger phrases: "extract action items from this transcript", "turn this chat export into tasks", "who owns what from this transcript", "AI transcript action table", "find decisions and deadlines in this text"

Example Prompts

  • "Paste a meeting transcript here: [user pastes text]. Extract all action items, owners, deadlines, decisions, and open questions into a reviewable register."
  • "Here's a long support chat export. Pull out every commitment, follow-up task, and unresolved issue. Separate confirmed decisions from suggestions."
  • "I have a project standup transcript. Turn it into a structured action table with owners, due dates, dependencies, and a verification checklist for me to review before sharing."

Required Inputs

Ask for or identify:

  • The pasted transcript, chat export, meeting notes, or excerpt
  • Meeting or discussion context, if available
  • Participant names and roles, if known
  • Date of the discussion, if known
  • Desired output format: table, bullets, CSV-style rows, or recap-ready register
  • Whether confidential, personal, regulated, client, HR, legal, medical, financial, or proprietary details need redaction

If the source text is missing, ask the user to paste the relevant text. Do not claim to access external transcripts or recordings.

Privacy and External AI Boundary

Before using or preparing text for any external AI tool:

  • Work only with pasted or user-provided text.
  • Redact confidential details before external AI use, including private names, client names, account identifiers, addresses, health details, financial details, legal details, HR details, credentials, and proprietary information.
  • Keep enough placeholder context for extraction, such as [CLIENT_A], [PROJECT_X], [PERSON_1], or [DATE_1].
  • Do not ask for passwords, credentials, one-time codes, secrets, private keys, or unnecessary personal data.
  • If the user cannot share the text safely, work from a summary they are allowed to provide.

Workflow

Step 1 - Confirm Source and Scope

Identify whether the input is a transcript, chat log, notes dump, excerpt, or mixed source. State whether it appears complete, partial, or fragmented. Mark missing context instead of guessing.

Step 2 - Redact or Minimize Sensitive Text

If the user asks to use external AI or the text contains sensitive information, create a redacted working version first. Preserve roles and relationships needed for task extraction while removing unnecessary confidential details.

Step 3 - Extract Candidate Actions

Find statements that imply a task, commitment, follow-up, request, blocker resolution, review, delivery, scheduling step, or handoff. Keep each action concrete and verb-led.

Step 4 - Assign Evidence and Confidence

For each candidate item, record the transcript cue or short paraphrase that supports it. Label confidence as confirmed, inferred, or needs verification.

Step 5 - Capture Owners and Dates Carefully

Extract owners and dates only when supported by the text. If an owner, date, or deadline is ambiguous, mark it as "needs verification." Do not infer ownership from seniority, speaking order, or convenience unless the user explicitly asks for a best-effort draft, and label it as inferred.

Step 6 - Separate Decisions From Tasks

List confirmed decisions separately from action items. Do not turn discussion, suggestions, or preferences into decisions unless the text clearly supports that a decision was made.

Step 7 - Identify Open Questions and Risks

Create separate lists for unresolved questions, blockers, dependencies, conflicting statements, missing owners, missing dates, and follow-up risks.

Step 8 - Build the Action Register

Produce a structured register with fields for action, owner, due date, source cue, dependency, status, confidence, and verification needed. Keep the table concise enough for review.

Step 9 - Add Manual Verification Checklist

End with a checklist reminding the user to verify owners, dates, task wording, decisions, redactions, and whether any sensitive content should remain removed before sharing or importing elsewhere.

Optional External AI Prompt

When the user wants a reusable prompt, provide a safe prompt template for redacted text only:

"Extract a reviewable action register from the redacted transcript below. Use only the provided text. Separate action items, confirmed decisions, open questions, risks, and items needing verification. For each action item, include action, owner, due date, source cue, dependency, confidence, and verification needed. Do not invent owners, dates, decisions, or consensus. Mark ambiguous items as needs verification."

Output Format

Use this structure:

  • Transcript Source Snapshot
  • Privacy and Redaction Notes
  • Action Register
  • Confirmed Decisions
  • Open Questions
  • Risks and Dependencies
  • Items Needing Manual Verification
  • Optional Follow-up Message or Import Notes
  • Verification Checklist

For the action register, use a simple table when the channel supports it. Suggested columns: Action, Owner, Due Date, Source Cue, Dependency, Confidence, Verification Needed.

Safety Boundaries

  • Work only from pasted or user-provided text.
  • Do not access private systems, files, recordings, calendars, email, messaging tools, or meeting platforms.
  • Do not fabricate actions, owners, deadlines, decisions, quotes, attendance, or consensus.
  • Redact confidential details before external AI use.
  • Verify owners and dates manually before assigning work or sending a recap.
  • For legal, medical, HR, disciplinary, financial, security, or safety-critical transcripts, recommend qualified human review before action.

Quality Bar

A strong result gives the user a visible, reviewable action register that separates confirmed work from uncertain items, preserves source support, protects sensitive details, and makes manual owner and date verification unavoidable.

常见问题

5 问
答案由本站依据条目字段整理
ai-transcript-action-extractor怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_15292d5a/yjkj-ai-transcript-action-extractor。安装方式为未标注。装完刷新技能列表或重开客户端。

ai-transcript-action-extractor支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

ai-transcript-action-extractor权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

ai-transcript-action-extractor收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

ai-transcript-action-extractor用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

热门专题

按场景挑技能
全部专题 →

技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。