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Agent Skill · 前端设计

blitzreels-clipping(闪电战剪辑)

blitzreels-clipping 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。

blitzreels-clipping 是前端设计类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描有提醒项,按安装量在前端设计类的 10,216 个 Skill 里排第 4,179。

总安装 964周安装 39GitHub Stars 公开资料未说明下载 303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:blitzreels-clipping(闪电战剪辑)
来源仓库:https://github.com/blitzreels/agent-skills
仓库路径:skills/blitzreels-clipping
安装命令:
npx skills add https://github.com/blitzreels/agent-skills --skill blitzreels-clipping
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/blitzreels/agent-skills --skill blitzreels-clipping

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

blitzreels-clipping 通过 /clips 资源统一管理视频剪辑全流程,包括转录、建议生成、排版与字幕合成。适合在 Codex、Claude、Cursor、Gemini CLI 中以状态机方式驱动剪辑任务,简化多阶段协作。

优先依赖 next_action 指引,而非手动调用底层端点;仅当 /clips 无法满足时才考虑低级接口。涉及外部资产或 YouTube URL 时,需确认版权许可与内容审核政策,避免侵权风险。使用前请检查 API 配额与计费模式,防止因高频调用产生意外费用或阻塞后续任务。

来源仓库内路径:skills/blitzreels-clipping

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/blitzreels/agent-skills --skill blitzreels-cli…;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

    它需要执行命令,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

blitzreels-clipping 怎么安装?

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

blitzreels-clipping 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。

blitzreels-clipping 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/blitzreels/agent-skills --skill blitzreels-clipping 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

blitzreels-clipping 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。

blitzreels-clipping 用的人多吗?

公开数据是累计安装 964 次,近一周安装 39 次,下载 303 次。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。

blitzreels-clipping 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

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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。
  • 需要处理前端设计类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
blitzreels-clipping

闪电战剪辑 · 本页

964—执行命令未明确有提醒

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

BlitzReels Clipping

Use the /clips resource as the primary clipping path. It wraps ingest, transcription, suggestion generation, layout, captions, and QA into a single state machine driven by next_action. The agent follows next_action rather than orchestrating individual stages.

The low-level staged endpoints (suggestion apply, preview-frames, timeline/media-views, etc.) exist for manual-control scenarios but should not be used unless the /clips resource cannot produce the result.

Canonical Endpoints

MethodPathPurpose
POST/clipsCreate a clip run from an asset or YouTube URL
GET/clips/{clip_id}Poll state — auto-advances through all stages
POST/clips/{clip_id}/reselectChange suggestion or set absolute time range
POST/clips/{clip_id}/repairRun one bounded repair pass
POST/clips/{clip_id}/exportExport a clip that is ready

User-Facing Workflow

Before creating a clip, let the user choose which segment to clip. This avoids wasting an API call on content the user doesn't want.

  1. Ingest and wait for suggestions. Create the clip with selection_mode: "auto_best" and poll until source.suggestions_status = "ready". The first poll response with suggestions will include selection.alternatives.
  2. Present suggestions to the user. Show the ranked list from selection.alternatives:

- title, hook, start/end timestamps, duration, score - Let the user pick one, or provide their own time range.

  1. If the user picks a different suggestion than auto_best selected, call POST /clips/{clip_id}/reselect with selection_mode: "suggestion" and the chosen suggestion_id.
  2. If the user provides manual timestamps, call POST /clips/{clip_id}/reselect with selection_mode: "time_range" and the absolute start_seconds + end_seconds.
  3. Continue the normal poll loop — follow next_action until export.

If the user says "just pick the best one" or doesn't express a preference, skip step 2 and let auto_best proceed.

Default Path

  1. Create the clip with POST /clips.
  2. Poll with GET /clips/{clip_id} while next_action = "poll".
  3. When suggestions are ready, present them to the user for selection (see above).
  4. If next_action = "reselect", pick another candidate from selection.alternatives or switch to a manual time range, then call POST /clips/{clip_id}/reselect.
  5. If next_action = "repair", call POST /clips/{clip_id}/repair once.
  6. If next_action = "export", call POST /clips/{clip_id}/export.
  7. Keep polling until status = "exported", status = "failed", or next_action = "stop".

The clip resource handles transcription, suggestion generation, reframe analysis, layout apply, captions, and QA internally. The agent never needs to call those endpoints directly.

Default Request

{
  "source": {
    "source_type": "youtube",
    "asset_id": null,
    "youtube_url": "https://www.youtube.com/watch?v=VIDEO_ID"
  },
  "selection": {
    "selection_mode": "auto_best",
    "suggestion_id": null,
    "start_seconds": null,
    "end_seconds": null
  },
  "target": {
    "aspect_ratio": "9:16",
    "max_duration_seconds": 75
  },
  "layout": {
    "layout_mode": "auto"
  },
  "captions": {
    "enabled": true,
    "style_id": "documentary"
  },
  "qa": {
    "qa_mode": "required"
  },
  "export": {
    "auto_export": false
  }
}

Overrides:

  • If the user gives an existing asset, use source_type: "asset" with asset_id.
  • If the user gives exact timestamps, use selection_mode: "time_range" with start_seconds and end_seconds.
  • If the user picks a specific suggestion, use selection_mode: "suggestion" with suggestion_id.
  • layout_mode: "auto" (default, evidence-based), "prefer_split" (forces dual-speaker split when evidence exists), "prefer_focus" (forces single-subject focus-cut).
  • qa_mode: "required" blocks export on QA failure; "permissive" allows export with warnings.

Caption style defaults:

  • documentary — default recommendation
  • full-sentence — sentence captions with active-word emphasis
  • single-word-instant — one-word-at-a-time captions
  • Any custom theme UUID from /caption-themes — use a theme ID created via the caption themes skill

Poll Fields

Read these fields on every GET /clips/{clip_id}:

  • status — current workflow state
  • next_action — what to do next (poll, reselect, repair, export, stop)
  • error — structured error with step, code, message, why_failed, how_to_fix, and retryable
  • source.analysis_status, source.analysis_version
  • source.transcript_status, source.suggestions_status
  • source.canonical_duration_seconds — best-available duration (max of transcript, suggestions, and asset metadata because any single source can be wrong)
  • selection.alternatives — ranked suggestion list with scores (present these to the user for selection)
  • clip_window — applied start/end/duration
  • layout.applied_mode, layout.primary_layout, layout.fallback_used, layout.warnings
  • captions.status, captions.clip_window_aware, captions.warnings
  • qa.status, qa.blocking, qa.issues, qa.preview_urls, qa.visual_debug_url
  • export.status, export.download_url, export.short_download_url

Suggestion Presentation Format

When presenting suggestions to the user, format each alternative clearly:

Example:

Here are the best moments I found:

1. "Why Most Startups Fail" (score: 0.92)
   0:45 – 1:58 (73s)
   Hook: The number one reason startups fail isn't what you think

2. "The Hiring Mistake" (score: 0.85)
   3:12 – 4:28 (76s)
   Hook: We hired 10 people in 2 weeks and it nearly killed us

3. "Product-Market Fit Signal" (score: 0.78)
   7:01 – 8:15 (74s)
   Hook: The moment we knew we had product-market fit

Which one would you like to clip? Or give me a custom time range.

Decision Rules

Fast path:

  • if qa.status = "passed" and next_action = "export", export

Blocked path — follow next_action, which will be one of:

  • "poll" when blocking_reason is source_not_ready, suggestions_not_ready, or analysis_not_ready — the clip resource is still auto-advancing through preparation stages
  • "reselect" when blocking_reason is invalid_selection (suggestion not found or time range invalid) or letterbox_rejected (planner couldn't achieve split/focus layout for podcast content — choose a different suggestion or time range)
  • "repair" when blocking_reason is visual_qa_failed — QA found critical framing issues. Run one repair pass, then poll. If still blocked after repair, next_action switches to "reselect"
  • "stop" when status is terminal (exported or failed)

Repair modes:

  • "auto" — recommended default, re-runs reframe planning
  • "prefer_split" — when the issue is speaker visibility in a podcast/interview
  • "prefer_focus" — when the issue is weak single-subject framing
  • "move_captions_off_faces" — when QA flagged caption-on-face overlap

Download URLs

The API returns two download URLs:

  • export.download_url — presigned S3 URL (long, expires in 1 hour)
  • export.short_download_url — clean redirect URL like https://www.blitzreels.com/api/v1/exports/{exportId}/download (requires auth header, 302-redirects to the presigned URL)

When presenting the download link to the user, prefer short_download_url for readability.

Reasoning Behind Key Constraints

  • Follow next_action, not assumptions: the clip resource's state machine handles stage sequencing internally. Asset existence does not mean transcript, suggestions, or analysis are ready — syncClip checks each gate on every poll and auto-advances when ready.
  • One repair pass, then reselect: the system caps automatic repair at one pass because repeated retries accumulate planner fallbacks (more letterbox segments) and degrade quality. After one repair, if QA still blocks, next_action switches to "reselect" so a different suggestion or time range can be tried.
  • Captions are clip-window-aware by default: the clip resource applies captions scoped to the selected clip window. Source transcripts can span an entire hour — without scoping, a 90-second short would render captions from unrelated parts of the video.
  • Letterbox rejection for podcasts: when layout_mode is "auto" and the planner can't achieve split/focus layouts (insufficient dual-speaker evidence), it rejects rather than silently exporting a low-quality letterboxed podcast clip.
  • Duration has three sources: asset metadata (often wrong — reports full video length even after trimming), suggestion timing, and transcript timing. canonical_duration_seconds takes the max of all three to avoid clipping content.

Output Contract

Return:

  • final_status: completed | blocked | failed
  • clip_id
  • project_id
  • next_action if not completed
  • blocking_reason if blocked
  • selected clip window
  • applied layout mode and whether fallback was used
  • captions status and whether clip-window-aware
  • QA status and issues
  • export status
  • short_download_url when exported (prefer this over download_url)

Manual-Control Fallback

When the /clips resource cannot produce the result (custom reframe plans, manual timeline edits, non-standard caption workflows), fall back to the staged endpoints. Read references/staged-endpoints.md for the full endpoint table and workflow.

References

  • Read references/recovery.md only when the clip is blocked or failed and next_action guidance is insufficient.
  • Read references/staged-endpoints.md only when manual-control fallback is needed.
  • Read examples/youtube-to-shorts.md only when a concrete execution example is needed.

平台分布

Codex

34.2%
按下载量换算104

Claude

29.72%
按下载量换算90

Cursor

19.39%
按下载量换算59

Gemini CLI

9.59%
按下载量换算29

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/blitzreels/agent-skills --skill blitzreels-clipping 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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