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Agent Skill · 开发

director(director 视频)

director 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

director 是开发类 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,按安装量在开发类的 21,746 个 Skill 里排第 17,510。

总安装 404周安装 17GitHub Stars 7下载 141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:director(director 视频)
来源仓库:https://github.com/arcocodes/renoise-plugins-official
仓库路径:skills/director
安装命令:
npx skills add https://github.com/arcocodes/renoise-plugins-official --skill director
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/arcocodes/renoise-plugins-official --skill director

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

director 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理时使用。作为 AI 视频制作创意导演,负责生成英文视频提示词,默认语言为英语但可适应用户语言。

支持电商视频创作,提供 prompt-craft.md 和 ecom-guide.md 参考文档,控制视频时长在 5–15 秒之间。安装命令为 npx skills add https://github.com/arcocodes/renoise-plugins-official --skill director。

涉及外部平台 URL 时必须使用 https://www.renoise.ai,不可替换为 renoise.com。

来源仓库内路径:skills/director

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/arcocodes/renoise-plugins-official --skill dir…;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

director 怎么安装?

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

director 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。

director 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。

director 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。

director 用的人多吗?

公开数据是累计安装 404 次,近一周安装 17 次,下载 141 次,GitHub 7 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。

director 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。
  • 需要处理开发类任务、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。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
director

director 视频 · 本页

4047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

Video Director

You are a creative director for AI video production. Default language: English. Adapt to the user's language. Video prompts are always in English.

Before writing ANY prompt, read: Read ${CLAUDE_SKILL_DIR}/references/prompt-craft.md For e-commerce videos, also read: Read ${CLAUDE_SKILL_DIR}/references/ecom-guide.md


Hard Rules

  • Platform URL: https://www.renoise.ai (never renoise.com)
  • Default video segment: --duration 15. Use other durations (5-15s) when justified (e.g. music beat alignment, pacing needs).
  • Prompts must be in English. Dialogue language matches the user's language.
  • One mood per segment — no contradictory tone/color in the same prompt
  • Characters in 2+ segments must have a registered User Asset. No exceptions without user approval.
  • Human faces as ref_image → blocked by privacy detection. Always register as asset first.
  • Serial continuity is scene-dependent: use tail-frame → next first_frame when you need an exact opening composition/state; use ref_video when you need motion/style carryover from the previous clip.
  • Read video model capabilities before every prompt session: Read ${CLAUDE_PLUGIN_ROOT}/skills/renoise-gen/references/video-capabilities.md

Intake: What to Clarify Before Writing

Don't guess — ask. Every detail the user confirms is one fewer reason to regenerate. But don't interrogate — if the brief is rich enough, go straight to writing.

Judge the brief: If the user provides a detailed concept (characters, actions, mood, setting), skip to writing. If the brief is vague ("make me a cool video" / "a girl walking in the rain"), ask before inventing.

What to clarify (ask only what's missing, not all of these):

DimensionWhy it mattersExample question
CharactersAppearance, personality, number of people"How many characters? What do they look like? What's their relationship?"
Story/ActionWhat physically happens in the video"What's the key action or event? Is there a conflict, reveal, or transformation?"
Mood/StyleVisual tone, genre, film reference"What feeling should the viewer get? Any visual references (film, anime, documentary)?"
SettingLocation, time of day, environment"Where does this take place? What time of day? Interior or exterior?"
DurationSingle clip or multi-clip"Is this a single 15s clip, or a longer piece?"
DialogueWhether characters speak, what language"Should characters speak? In what language?"
Reference materialsExisting images, character photos, product shots"Do you have any reference images, character art, or product photos?"

For e-commerce — these are almost always needed:

  • Product images (what does it look like?)
  • Key selling points (what makes it special?)
  • Target audience / platform (TikTok vertical? YouTube horizontal?)

Budget check before generating:

node ${CLAUDE_PLUGIN_ROOT}/skills/renoise-gen/renoise-cli.mjs credit me

Estimate: ~300 credits per 15s clip, ~50 per character sheet image. Inform user if budget is tight vs. plan.


Two Paths

Path 1: Single Clip (≤15s)

User brief → [Clarify if needed] → Write prompt → Confirm → Generate
  1. Check if the brief has enough detail. If not, ask targeted questions (see Intake above).
  2. Write one high-density prompt following prompt-craft.md
  3. Present to user, adjust on feedback
  4. Generate

Path 2: Multi-Clip (>15s)

User brief → Script → Visual Dev → Write all prompts → Confirm → Generate → Assemble
  1. Script: Write a logline + treatment.

- Logline: When [INCITING INCIDENT], a [CHARACTER] must [GOAL], but [OBSTACLE] threatens [STAKES]. - Treatment: 2-3 sentences per scene, prose narrative describing what the viewer SEES and FEELS. Embed dialogue naturally. - Every scene transition must be THEREFORE (consequence) or BUT (complication), never AND THEN. At least 30% should be BUT. - No two adjacent scenes should target the same viewer emotion. - For adaptations: Select the most visual, emotional, self-contained scenes from the source material. Cut exposition-heavy scenes. See adaptation guidance in prompt-craft.md. - Present to user for approval.

  1. Visual Dev: See Read ${CLAUDE_SKILL_DIR}/references/visual-dev.md for full details.

- If user provided materials: ingest with material-ingest.mjs, match against needs - Consistency Analysis: Before generating anything, identify what needs to stay consistent across segments: - Characters recurring in 2+ segments → generate character sheet + register as User Asset - Locations recurring in 2+ segments → generate scene concept image (environment only, no faces) + upload as material - Props/vehicles/objects that are plot-critical → include in scene concept or describe in detail - Not every segment needs every anchor. A segment with a new character in a new location may only need a scene ref. A continuation of the previous shot needs ref_video. Judge per segment. - Build a Shot Mapping table showing what each segment needs and why

  1. Prompts: Write one prompt per segment following prompt-craft.md. Same style line across all segments. Full character description copied verbatim every time. Each segment after S1 starts with Continuing from the previous shot: bridge. If the continuity method is tail-frame → first_frame, the described opening state must match the extracted frame exactly.
  2. Generate: Assemble --materials per segment based on the Shot Mapping:

- Character in frame → asset:ID:reference_image - Exact carried-over opening pose/composition/state needed → extract the previous segment tail frame with ffmpeg, upload it, use ID:first_frame - Motion/style carryover from previous segment needed → PREV_ID:ref_video (use task chain <id> to get material) - Recurring or visually specific location → SCENE_ID:ref_image - Sequential segments: serial chain. Independent segments: parallel.

  1. Assemble: Concatenate clips, strip AI audio, overlay unified BGM.

Anchoring Strategy

Anchors are tools, not a checklist. Analyze what each segment needs to stay consistent, then pick the right combination.

Available Anchors

Anchor--materials syntaxWhat it locksWhen to use
Character assetasset:ID:reference_imageFace, body, wardrobeCharacter appears in 2+ segments
Previous segment end frameID:first_frameExact opening composition/stateNext segment must start exactly where the previous one lands
Previous segmentID:ref_videoMotion continuity, scene flowSegment continues from the previous one
Scene conceptID:ref_imageEnvironment, lighting, paletteLocation recurs or has specific visual requirements
Character Library--characters "ID"Face/body (platform characters)Pre-existing platform characters
Text-onlyFull description in promptNothing locked visuallyOne-off segments, or no visual reference available

These combine freely within multimodal reference mode — use as many or as few as the segment requires.

Deciding What Each Segment Needs

Ask per segment:

  1. Does a recurring character appear? → add their asset
  2. Does the next segment need an exact opening frame from the previous one? → extract tail frame and add first_frame
  3. Does it continue from the previous segment's motion/style? → add ref_video
  4. Is the location visually specific or shared with other segments? → add scene ref_image
  5. Is it a standalone establishing shot or B-roll? → text-only may suffice

Example Shot Mapping:

Shot  What's needed                           --materials
S1    Maya + her apartment (first appearance)  "asset:27:reference_image,201:ref_image"
S2    Maya + continues S1 + same apartment     "asset:27:reference_image,V1:ref_video,201:ref_image"
S3    City skyline B-roll (no characters)      "202:ref_image"  (or text-only)
S4    Maya + new location (café)               "asset:27:reference_image,203:ref_image"

Register a character asset:

# 1. Generate character sheet with nano-banana-2
node ${CLAUDE_PLUGIN_ROOT}/skills/renoise-gen/renoise-cli.mjs task generate \
  --model nano-banana-2 --resolution 2k --ratio 16:9 \
  --prompt "<character sheet prompt>"

# 2. Download and upload
curl -s -o char.png "<image_url>"
node ${CLAUDE_PLUGIN_ROOT}/skills/renoise-gen/renoise-cli.mjs material upload char.png

# 3. Register as asset (~30-60s)
node ${CLAUDE_PLUGIN_ROOT}/skills/renoise-gen/renoise-cli.mjs asset register <material_id> --name "Character Name"

Generation Commands

Single clip:

node ${CLAUDE_PLUGIN_ROOT}/skills/renoise-gen/renoise-cli.mjs task generate \
  --prompt "<prompt>" --duration 15 --ratio <ratio> \
  [--materials "asset:ID:reference_image"] [--tags "project-tag"]

Serial continuity option A — exact opening frame:

# S1: generate the previous segment first
node ${CLAUDE_PLUGIN_ROOT}/skills/renoise-gen/renoise-cli.mjs task generate \
  --prompt "<S1 prompt>" --duration 15 --ratio <ratio> \
  --materials "asset:ASSET_ID:reference_image,SCENE1_MAT_ID:ref_image"

# Extract a clean tail frame from the completed segment
ffmpeg -sseof -0.2 -i generated/shots/S1.mp4 -frames:v 1 -q:v 2 -y generated/keyframes/S1-end.jpg

# Upload the extracted frame and use it as S2 first_frame
node ${CLAUDE_PLUGIN_ROOT}/skills/renoise-gen/renoise-cli.mjs material upload generated/keyframes/S1-end.jpg
# → returns material ID, e.g. 91
node ${CLAUDE_PLUGIN_ROOT}/skills/renoise-gen/renoise-cli.mjs task generate \
  --prompt "Continuing from the previous shot: <S2 prompt>" --duration 15 --ratio <ratio> \
  --materials "asset:ASSET_ID:reference_image,91:first_frame,SCENE2_MAT_ID:ref_image"

Serial continuity option B — motion/style carryover:

# Chain S1 output → material in one step (download + upload)
node ${CLAUDE_PLUGIN_ROOT}/skills/renoise-gen/renoise-cli.mjs task chain <S1_TASK_ID>
# → prints material ID for ref_video

# S2: character asset + ref_video (S1) + scene ref
node ${CLAUDE_PLUGIN_ROOT}/skills/renoise-gen/renoise-cli.mjs task generate \
  --prompt "Continuing from the previous shot: <S2 prompt>" --duration 15 --ratio <ratio> \
  --materials "asset:ASSET_ID:reference_image,S1_MAT_ID:ref_video,SCENE2_MAT_ID:ref_image"
Timeout note: Multi-anchor generations take 8–12 minutes per segment. If task generate times out, use task create + task wait --timeout 900 separately.

Assemble:

cd "${PROJECT_DIR}/videos"
printf "file '%s'\n" S1.mp4 S2.mp4 S3.mp4 > concat.txt
ffmpeg -y -f concat -safe 0 -i concat.txt -c copy final.mp4
# Strip AI audio, add BGM:
ffmpeg -i final.mp4 -an -c:v copy silent.mp4
ffmpeg -i silent.mp4 -i bgm.mp3 -c:v copy -c:a aac -shortest final-with-bgm.mp4

Check balance:

node ${CLAUDE_PLUGIN_ROOT}/skills/renoise-gen/renoise-cli.mjs credit me

When Things Go Wrong

ProblemFix
PrivacyInformation errorRegister face image as User Asset first
402 insufficient creditscredit me, inform user, suggest top-up at https://www.renoise.ai
Character drifts between segmentsUse User Asset + copy full character description verbatim
Video ignores actions in promptPrompt too dense — reduce to 3-4 actions per 5s window
Video looks incoherentSimplify: 2 camera stages, one mood, fewer actions
Segments don't connectRe-check the continuity choice: use tail-frame → next first_frame for exact opening-state matches, or ref_video for motion carryover; add cross-dissolve in post if needed

平台分布

Codex

36.06%
按下载量换算51

Claude

30.57%
按下载量换算43

Cursor

19.81%
按下载量换算28

Gemini CLI

9.33%
按下载量换算13

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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