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Agent Skill · 研究检索

audify(audify 搜索)

audify 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

audify 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,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 71,089。

总安装 196周安装 8GitHub Stars 13下载 63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:audify(audify 搜索)
来源仓库:https://github.com/jpcaparas/skills
仓库路径:skills/audify
安装命令:
npx skills add https://github.com/jpcaparas/skills --skill audify
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/jpcaparas/skills --skill audify

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。

audify 将文本或网页资源清洗后合成为语音文件,输出带时间戳的 MP3 与元数据。适用于需要将长文档、研究报告转为音频内容的场景,如播客素材准备。自动过滤代码、表格等不适合朗读的内容,保留可读性强的叙述段落。使用时应指定输入类型(URL、Markdown、DOCX 等),系统选择合适处理路径。

依赖 Gemini TTS API,需注意字数限制与 API 调用配额管理。

来源仓库内路径:skills/audify

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/jpcaparas/skills --skill audify;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

    它需要需要联网,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

audify 怎么安装?

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

audify 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。

audify 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

audify 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。

audify 用的人多吗?

公开数据是累计安装 196 次,近一周安装 8 次,下载 63 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。

audify 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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
audify

audify 搜索 · 本页

19613需要联网未明确有提醒

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

audify

Clean a readable resource into narration-safe prose, synthesize it with Gemini 3.1 Flash TTS, and write a timestamped output folder that contains an MP3, the cleaned transcript, and a manifest.

Verified against the Gemini API speech generation docs updated April 15, 2026 and the Google Cloud blog post published April 16, 2026.

Decision Tree

What kind of input are you handling?

  • A URL, markdown file, HTML file, DOCX, plain text file, or raw text that should be listened to

- Run python3 scripts/audify.py...

  • A resource that is mostly code, logs, tables, minified JSON, or other content that is not meant to be narrated

- Bail instead of forcing TTS. Explain why it is not a good narration target.

  • A request where voice or nuance is materially ambiguous

- Ask one short question before synthesis. - Use: "Which voice and delivery should I use? If you do not care, I will use Kore with a clear neutral narrator style."

  • A request where the user does not care about style details

- Default to Kore plus a clear neutral narrator nuance.

  • A longer job with multiple chunks or a large cleaned transcript

- Tell the user up front that multi-chunk TTS can take a few minutes and that quiet periods are normal. - Do not keep narrating every short poll. Prefer one expectation-setting update, then wait for chunk progress or completion.

  • Missing GEMINI_API_KEY, unavailable gemini-3.1-flash-tts-preview, missing ffmpeg, or exhausted read attempts

- Bail with the concrete failed prerequisite.

Quick Reference

TaskCommandRead
URL to MP3 bundlepython3 scripts/audify.py "https://example.com/"references/patterns.md
Local file to MP3 bundlepython3 scripts/audify.py --file templates/sample-input.md --voice Kore --nuance "Warm documentary narrator"references/patterns.md
Raw text from stdin`cat templates/sample-input.md \python3 scripts/audify.py --stdin`references/patterns.md
Clean-only suitability checkpython3 scripts/audify.py --url "https://example.com/" --check-onlyreferences/patterns.md
Live model and synthesis probepython3 scripts/probe_gemini_tts.py --mode allreferences/api.md

Reading Guide

If the user needs...Read
Raw Gemini REST shape, supported models, voices, and failure codesreferences/api.md
Env vars, key setup, ffmpeg, and prerequisite checksreferences/configuration.md
URL/file/text workflows, output bundle layout, and question-asking rulesreferences/patterns.md
Failure handling, retries, and why audify should bailreferences/gotchas.md

Operational Rules

  1. Treat SKILL.md as the entry point and keep the tool choice narrow: scripts/audify.py for production runs, scripts/probe_gemini_tts.py for live verification.
  2. Clean first, synthesize second. Strip markup, HTML, code fences, and bare URLs before TTS so the spoken transcript stays close to the readable text instead of the transport format.
  3. Preserve human text whenever possible. Keep visible anchor text, headings, paragraph content, and inline prose; drop boilerplate that is structural rather than spoken.
  4. Stop when the source is not narration-friendly. Do not read code dumps, logs, stack traces, raw tables, or binary blobs aloud just because they decoded as text.
  5. Stop when read attempts are exhausted. Do not silently fall back from a bad fetch or undecodable file to a hallucinated summary.
  6. Set runtime expectations before long runs. For multi-chunk TTS, tell the user a realistic range such as "often 2-6 minutes" and that silence between chunk completions is normal.
  7. Do not badger the user with polling updates. After the initial expectation-setting message, only report meaningful state changes such as chunk progress, retries, or final completion.
  8. Auto-split large transiently failing chunks before giving up. Keep the same voice, nuance, model, and output format while retrying with smaller chunk boundaries.

Output Contract

By default scripts/audify.py creates audify-output/<timestamp>-<slug>/ under the current working directory.

The folder contains:

  • audio.mp3 by default
  • cleaned.txt with the final spoken transcript
  • manifest.json with source, voice, nuance, chunking, and retry metadata
  • runtime expectations in both the wrapper output JSON and the status stream
  • fallback chunk-split metadata when a large chunk had to be retried in smaller pieces

Use --format wav when MP3 conversion is not wanted.

Gotchas

  1. Gemini TTS returns PCM, not MP3: The Gemini API returns base64 PCM audio. This skill converts it locally with ffmpeg, so missing ffmpeg is a hard stop for the default MP3 path.
  2. Gemini 3.1 Flash TTS can throw transient 500 errors: Google documents rare cases where the model emits text tokens instead of audio tokens. The wrapper retries transient failures with backoff.
  3. Vague prompts can get rejected or spoken aloud: The wrapper uses an explicit "synthesize speech only" preamble and a labeled TRANSCRIPT section so instructions do not become narration.
  4. Voice and prompt can clash: Google warns that strong speaker mismatches can sound wrong. When the user asks for a very specific persona, make sure the selected voice and nuance point in the same direction.
  5. HTML extraction is best-effort: Blog chrome, nav text, or legal footer text can still leak through on messy pages. If the cleaned preview looks wrong, stop and ask for a narrower source.
  6. Long silence is not the same as failure: A multi-chunk run can spend a couple of minutes inside Gemini calls and local MP3 conversion. Do not treat every quiet 30-second interval as a problem.
  7. A single large chunk can still fail transiently: When that happens, the wrapper should split just that chunk into smaller pieces and continue with the same voice, nuance, model, and format instead of forcing a full manual rerun.

Helper Scripts

  • scripts/audify.py is the production wrapper for URL, file, stdin, and raw text inputs.
  • scripts/probe_gemini_tts.py runs safe live probes against model discovery and short synthesis.
  • scripts/test_audify_unit.py covers cleaner, chunking, DOCX extraction, and bail heuristics.
  • scripts/validate.py checks structure, cross-references, and leftover template placeholders.
  • scripts/test_skill.py runs structural checks, unit tests, and a live smoke probe when GEMINI_API_KEY is present.

平台分布

Codex

35.36%
按下载量换算22

Claude

30.25%
按下载量换算19

Cursor

20.57%
按下载量换算13

Gemini CLI

9.77%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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