Env Setup

SKILL内容创作
内容创作 未标注权限 许可证不明确

Checking and provisioning the machine's environment for the video-agent-kit plugin — probing for ffmpeg/ffprobe that actually carry the encoders and filters we render with (libx264/aac/libmp3lame, libass, libfreetype), python packages (mcp, cv2, numpy, PIL, jieba, fontTools, scenedetect) in the interpreter Claude Code really uses, a CJK font whose cmap truly covers Chinese, and which speech channel is in play (under ZCode the official channel needs no local key) — then installing what is missing (China mirrors by default) or telling the user exactly what to install. Works on macOS, Windows and Linux. Use BEFORE the first edit run on a new machine, when the session-start hook reports 缺失依赖, or whenever a tool fails in an environment-shaped way — ModuleNotFoundError, `ffmpeg not found`, `Unknown encoder 'libx264'`, `No such filter: 'subtitles'`, `no font file found for family`, 字幕烧成豆腐块/方块, speech_transcribe 超时或 401. Also use when asked to 检查环境 / 装依赖 / 配国内源 / setup / doctor.

一句话选型结论

按资料字段整理

Env Setup是内容创作类的 Agent Skill,安装方式:GitHub 仓库,权限级别未标注,许可证不明确,没有现成安装命令,需按说明手动放置 SKILL.md。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。

分类内容创作 安装方式GitHub 仓库 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 skills_collection
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

GitHub 仓库
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
  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

    按安装说明或仓库 README,把 SKILL.md 放到客户端的 skills 目录(一般一个技能一个文件夹)。

  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

内容创作
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wwwzhouhui仓库 skills_collection · 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GitHub 仓库安装包 wwwzhouhui/skills_collection
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 2026-08-29
正文体量13.9 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
写文章与脚本

按主题产出初稿与分镜脚本。

改稿与润色

把草稿改顺、统一语气。

多平台文案改写

同一内容按平台改成长短不同的版本。

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

  • 基础信息齐全,可以先按说明装一个试试。

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。
  • 没有现成安装命令,要按安装说明或仓库 README 手动放置。
  • 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

  • 需要在内容创作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
Env Setup当前 未标注权限 GitHub 仓库 未标注 未标注 无
AI 视频生成 调用外部服务 GitHub 仓库 431.3 万 Codex、Claude、Cursor 有
视频帧 联网访问 ClawHub 市场 262.1 万 OpenClaw 有
Markdown 转换器 写入文件 ClawHub 市场 135.3 万 OpenClaw 有
哔哩哔哩全合一 接触敏感数据 ClawHub 市场 64.1 万 OpenClaw 有
Remotion video toolkit 命令行 浏览器控制 ClawHub 市场 63.9 万 OpenClaw 有

SKILL.md 全文

13.9 KB
模型实际读到的说明书原文,来自技能仓库

Env Setup

Claude Code is a generic harness — it ships no ffmpeg, no CJK font, no python
media stack. Everything this kit needs is per-machine, and provisioning it is
this skill's job. A run started on a half-provisioned machine does not fail
cleanly: it burns the whole observe→timeline phase and then dies at
render_preview, or worse, succeeds while burning subtitles as tofu boxes
(□□□) because fc-match handed us a font with no Chinese glyphs and ffmpeg
exited 0.

One entry point — everything else here is judgement about its output:

python3 <plugin_root>/skills/env-setup/scripts/env_doctor.py          # probe + what's needed
python3 <plugin_root>/skills/env-setup/scripts/env_doctor.py --fix    # + install the auto-safe items

(Windows: python instead of python3 if that's what's on PATH.) Plugin root is
announced at session start and written to .video_agent/plugin_root. Always call
it by absolute path — cwd is the project directory, not the skill directory. A
full probe is a few seconds; give Bash ≥ 120s anyway, because a blocked network
spends its timeouts before answering.

What must be present, and what dies without it

The script decides state and prints the exact requirement + an example command
for the current OS. This table is only for judging impact:

Requirement Dead without it
Python ≥ 3.10, and mcp (1.x), requests, opencv-python-headless, numpy, pillow, jieba, fonttools, scenedetect in that same interpreter mcp → every tool (server won't start); requests → transcribe + all TTS; cv2/numpy/PIL → video_ingest, contact sheets, qc_preview scans, i.e. all visual evidence; jieba → subtitle_build line breaking; fontTools → the pre-render tofu check; scenedetect → recap shot boundaries
ffmpeg + ffprobe on PATH, with libx264 / aac / libmp3lame ingestion and probing (Phase 1 can't start); missing encoder = the render dies at the last step, after everything upstream was paid for
that ffmpeg built with libass + libfreetype (subtitles/ass/drawtext filters) subtitle burn-in, title cards, score bugs — the recap deliverable
a CJK font whose cmap really covers Chinese Chinese subtitles/titles. This one fails silently — see the tofu warning above
cloud ASR credentials or Speech MCP access speech_transcribe; without it there is no transcript, so every speech-driven decision is guesswork. Under ZCode this is never a gap — see below
cloud TTS credentials or Speech MCP access narration/dubbing (speech_synthesize, tts_generate, *_tts). Edit-only and subtitle-only tasks survive without it

Speech needs no local key under ZCode

Transcription and synthesis default to the official channel, which authenticates
with identity the ZCode host injects into each tools/call. There is nothing to
configure, nothing to install, and no key to obtain. Two consequences:

  • Never tell the user to set an ASR/TTS key to get transcription working, and
    never treat a "credentials not set" line as a blocker. The doctor reports these
    two rows as 官方通道 whenever ZCODE_BASE_URL is present, and both rows are
    soft (只降级不致命) in every case.
  • The doctor runs as its own process, so it cannot see the per-call identity
    headers — only whether the official channel exists at all. A specific call
    failing on identity (not logged in, no Coding Plan) surfaces from the tool
    itself, with a message saying which of the two it is. That is the signal to act
    on; the doctor's row is not.

Only non-ZCode hosts need configuration, in this order of preference: remote
Speech MCP (VE_SPEECH_MCP_URL / VE_SPEECH_MCP_TOKEN), or — as a legacy escape
hatch for deployments bringing their own speech service — a direct HTTP backend,
which needs its endpoint and resource/model identifiers in the process
environment
(a project .env is untrusted for those; it could otherwise
redirect an authenticated call) plus a key. /env-check prints the exact set.

Version floors are the only hard numbers; how the tool gets installed is the
user's choice — package manager, installer, conda, whatever the machine already
uses.

Mirrors — use them by default, not as a fallback

Most users of this plugin are in mainland China, where the official PyPI CDN and
GitHub-hosted Homebrew bottles are routinely slow enough to time out. A timeout
there doesn't look like a network problem — it looks like "the install ran for
ten minutes and then failed", which gets misdiagnosed as a broken package every
time. So a mirror is the first choice, not the recovery step. The doctor
already puts the mirror into the command it prints (and uses); when you install
by hand, use these:

What First choice Alternative
pip 清华 https://pypi.tuna.tsinghua.edu.cn/simple — pip install -i https://pypi.tuna.tsinghua.edu.cn/simple <pkg> 阿里云 https://mirrors.aliyun.com/pypi/simple/
ffmpeg macOS: export HOMEBREW_BOTTLE_DOMAIN=https://mirrors.tuna.tsinghua.edu.cn/homebrew-bottles then brew install ffmpeg. Any platform / no root: conda install -c https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge ffmpeg — cleanest path, no system package manager touched. apt sources → Tsinghua/USTC (system-wide change); Windows winget/gyan.dev has no mirror concept (use conda)
CJK font Linux apt-get install fonts-noto-cjk (apt mirror helps). mac/Windows already ship 苹方/微软雅黑 — install nothing. Download NotoSansSC from github.com/notofonts/noto-cjk into any directory and point VE_FONT_DIRS at it (works without root)
direct speech endpoint (only if you configured one) no mirror exists — it is the service itself. Unreachable = network policy; that's a proxy question, not a mirror one —

Notes that matter in practice:

  • Making it permanent is the user's call, not yours by default:
    pip config set global.index-url <url> writes their global config and
    affects every other project on the machine. The doctor prints it; only run it
    if the user agrees — a one-off -i <url> needs no such permission.
  • Mirrors lag. If a package version genuinely isn't on the mirror, the fix is
    to drop -i for that one install and go to the official source — not to
    conclude the environment is broken.
  • Outside mainland China these mirrors are pointless (and slower).
    VE_PIP_INDEX=<url> overrides the pip index the doctor uses; set it to the
    official URL to opt out entirely.
  • A mirror fixes slowness, a proxy fixes blockage — different problems. Try
    the mirror first; only if the mirror itself is unreachable is it a
    proxy/firewall question.

Workflow

doctor → read the requirements → --fix the auto items → tell the user what's left → re-run doctor → report

  1. Run the doctor first, always. Never install from this file's tables or
    from memory — on a provisioned machine the correct action is nothing, and a
    speculative install can downgrade a working package (or, with opencv, break
    the one that worked).
  2. --fix covers only the user-space, idempotent subset: pip installs into
    the running interpreter. It deliberately does not install ffmpeg, fonts,
    or uninstall anything — those are system-level or destructive, the right
    method differs per machine (and per permission level), and guessing wrong is
    worse than reporting. For those, give the user the requirement and the
    suggested command, and let them run it.
  3. Fix in the printed order. An item whose prerequisite failed prints
    [未探测] instead of a guessed verdict — don't run a fix for an unprobed
    item; fix its prerequisite and re-run.
  4. · means "not applicable on this OS", not "broken", and
    只降级不致命 means exactly that: the two speech-channel rows and disk headroom
    don't block a task. Everything else is a hard gap.
  5. After a PATH-changing install, the new tool is invisible to the current
    shell
    (most visibly on Windows). If the doctor still can't see ffmpeg the
    user just installed, that's the reason — have them restart the terminal (or
    Claude Code) rather than reinstalling.
  6. Re-run the doctor at the end — not the fix commands' exit codes.
    pip install can succeed while the import still fails (a wheel mismatched to
    the platform). The run writes .video_agent/env_report.json as the receipt,
    so don't re-probe every turn; re-probe after installing something or
    after a tool fails.
  7. Report in capability terms, then stop if something's dead. "ffmpeg has no
    libass → subtitle burn-in unavailable; the recap can't ship. Install a full
    build and re-run /env-check." Do not enter a phase whose tools are dead and
    improvise around it.

Rules

  • Install only what the doctor flagged. Extra packages are how a working
    environment drifts into an unreproducible one.
  • Never substitute for a missing dependency. No cv2 does not mean "extract
    frames with ffmpeg and eyeball the filenames"; no transcript does not mean
    "infer the dialogue from the visuals"; no CJK font does not mean "render the
    subtitles in English". A dead capability is a report line, not a workaround.
  • scenedetect must be installed with --no-deps. It declares
    opencv-python (the GUI build), which overwrites the same cv2 package
    directory as opencv-python-headless and leaves both half-broken. The doctor
    prints the two-step command; don't "simplify" it.
  • Never auto-uninstall opencv. If GUI+headless are both installed the doctor
    reports it and prints the fix, because the GUI build may belong to another
    project on that machine. That's the user's call.
  • A font that resolves is not a font that works. fc-match never fails: ask
    it for an uninstalled Chinese family and it returns DejaVu Sans, which has no
    CJK glyphs, and libass then renders blanks while ffmpeg exits 0. The doctor
    reads the cmap for exactly this reason — if it says the resolved font has no
    Chinese coverage, treat it as missing even though a path was printed.
  • Adding a dependency to this plugin means adding a Check to
    env_doctor.py in the same change
    (and to requirements.txt). The
    SessionStart hook imports cheap_missing() from it, so the cheap checks are
    the single source of truth for the startup warning — a dependency that isn't a
    Check is one nobody hears about until it crashes.

Fonts: the one platform difference worth knowing

Font lookup is centralised in mcp/ve_tools/fonts.py, searched in this order:

  1. VE_FONT_DIRS (os.pathsep-separated) — explicit override, always wins
  2. the Linux dirs the kit has always used (/root/.fonts, /usr/share/fonts)
  3. the platform's own font dirs — /System/Library/Fonts, ~/Library/Fonts
    (macOS), %SystemRoot%\Fonts, %LOCALAPPDATA%\Microsoft\Windows\Fonts
    (Windows)
  4. fc-list :lang=zh when fontconfig exists, cmap-verified

So macOS and Windows normally need no font install at all (苹方 / 微软雅黑
are found in step 3, and libass resolves them through CoreText/DirectWrite).
Linux images without fonts-noto-cjk are the case that actually needs work.
When a user has fonts somewhere unusual, VE_FONT_DIRS is the answer — not a
code change, and not sudo cp into /usr/share/fonts.

Anti-patterns

  • Prescribing one platform's install method (apt-get …) to a user on another OS
    — the doctor already picked the right example for their machine; if they'd
    rather use their own method, that's fine, the requirement is what matters.
  • Reading this skill's tables and installing from them without running the doctor.
  • Treating a [未探测] line as a missing dependency, or a · (n/a) line as a defect.
  • Auto-installing system-level software (ffmpeg, fonts) or uninstalling packages
    on the user's machine without being asked.
  • Retrying a stalled pip install unchanged on a machine that needs a mirror
    (or a proxy) — the second attempt fails the same way, ten minutes later.
  • Declaring the environment fixed off exit codes without a re-probe.
  • Re-running the full doctor every turn "to be safe" — .video_agent/env_report.json
    holds the last verdict.
  • Proceeding into a render or a recap with ffmpeg missing libass, letting it
    surface as a mysterious tool error twenty rounds later.
  • Asking the user for an ASR/TTS key. Under ZCode there is no key to give;
    the doctor's speech rows say 官方通道 and a failing call reports whether it is
    a login or a plan problem. Chasing a key wastes the user's turn and fixes nothing.
  • Blaming the plugin for speech_transcribe timeouts before checking which
    channel it used — an unreachable configured direct endpoint is a network
    policy problem no amount of retrying fixes, and it is not even consulted when
    the official channel or a remote Speech MCP is in play.

常见问题

5 问
答案由本站依据条目字段整理
Env Setup怎么安装?

没有现成安装命令:按安装说明或仓库 README,把 SKILL.md 放进客户端的 skills 目录(一般一个技能一个文件夹)。

Env Setup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。

Env Setup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。

Env Setup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。

Env Setup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。

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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。