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blitzreels-clipping闪电战剪辑

Agent Skill

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。

总安装

964

周安装

39

GitHub Stars

公开资料未说明

下载量

303
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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.

适合场景

01

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02

需要根据任务场景推荐可安装能力包时

03

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能力 2

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能力 3

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能力 4

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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

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