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edit-timeline-studio

価格未確認★ 792 GitHub スター登録情報の更新日 · 2026年9月17日agent-skill

概要

Analyze images, video, speech, motion, products, and websites; route local vision, audio, depth, tracking, matting, identity, and restoration models; auto-edit, replicate, enhance, caption, voice, assemble, validate, and export editable Timeline Studio projects and videos. Use for reference-video remakes, filter and repeated-shot reconstruction, subject-aware reframing, clip splitting, source-time speed curves, Color Wheels grading, ramps and holds, person or product cutout, person or object outline, authorized face swap, shot and timing reconstruction, supplied or web-sourced footage, AI video platform selection, cleanup, highlights, product promotion, website walkthroughs, image-to-video assisted edits, optical-flow editing, depth/2.5D/transition finishing, AI voiceover, subtitles, short-form production, .timeline automation, or editor evaluation.

説明全文を読む

ソース文書であり、このサイトへの操作指示ではありません。コマンド実行前に権限を確認してください。

AI Video Editing with Timeline Studio

Turn the user's exact editorial request and media into reversible Timeline Studio edits. Keep the editable timeline as the source of truth; never replace it with an opaque one-shot render.

Choose the execution path

On first local use after installation, read references/host-environment.md. If Node.js is unavailable, start with the zero-dependency Shell or PowerShell bootstrap; otherwise run node scripts/setup-host.mjs --check. Agent-driven Chinese and mixed Chinese/English voiceover uses Timeline Studio's owned browser-local Hojo TTS Light 80M two-voice bundle and does not require a separate Python voiceover capability. If language runtimes or dependencies are missing, show the exact installation plan and obtain explicit user approval before install mode; never treat Skill installation as permission to modify the host or download models.
Treat local project-file processing as the default for deterministic editing: inspect media locally, modify the portable .timeline through the command layer or local archive services, and render and verify decoded output when the task changes rendered media. Do not open a browser merely because the editor has a UI.
Treat https://video-editor.ai-creator.top/ as the canonical hosted editor only when the user explicitly asks to use the website, provides no local repository or project path, or requires a hosted-only capability.
When this repository is available, prefer its Agent command layer and local media tools. Start the local server and browser only for a verified UI-only operation that the local project pipeline cannot express and the user has not required a local-only workflow. Read the actual server URL from process output; never assume port 5173.
Prefer the bundled Timeline Studio MCP tools when the host exposes them. Read references/mcp-integration.md, inspect the project, and always call timeline_project_diff before timeline_project_apply with the same revision and operations. The MCP server is a transport over the repository command runner, not a separate editing implementation.
When MCP is unavailable, inspect package.json for an Agent command script. Do not use npm run ... --if-present as capability detection because it can succeed silently. If the command runner exists, read references/command-contract.md, inspect the project, build a versioned plan, run the structural validator, and use project.diff as the authoritative semantic dry run before project.run.
If a required operation is missing from the local contract, state the exact gap. For repository-development work, implement the smallest shared local operation and renderer support before falling back to UI. Otherwise ask before switching to the browser workflow.
Do not claim deterministic or idempotent execution when only UI automation was available. State the limitation and preserve an editable project archive when the UI supports it.

Workflow

For a marker-only request, read references/timeline-markers.md and follow its inspect → plan → validate → diff → apply → inspect workflow through annotation handoff. Markers, chapter cues, ranges, and notes are project annotations; adding them requires no narration, model download, browser session, or video render. The media-production steps below apply only when the user also requests a media edit.

1. Inspect before editing

Preserve the user's prompt verbatim as the creative brief.
Resolve every referenced asset to an explicit path or URL. Never sweep a directory without approval.
Inspect duration, dimensions, audio presence, and media type.
Read the current project summary before changing an existing project.
Before planning long videos, chapters, musical beat cues, review notes, or edit ranges, read references/timeline-markers.md. Inspect existing annotations and use evidence-backed markers to preserve editorial anchors and decisions where useful. Preserve user annotations and distinguish Agent observations from supplied feedback.
Ask only when an unresolved choice materially changes the edit, such as the desired output duration or aspect ratio.
For an automatic-editing request, read references/auto-edit-workflow.md. Inspect first, classify the content, goal, and delivery with an explicit confidence level, then ask only the minimum category-specific questions that can change the cut. Never ask for facts discoverable from the media.
For a request to reproduce, imitate, recreate, or reverse-engineer a reference video, read references/replication-workflow.md. Classify it as editing-style replication, AI-generation replication, or a hybrid; reconstruct filters, repetitions, source splits, speed curves, transitions, shots, and timing before building; and explicitly resolve whether the authorized original audio track must be retained. Do not start editing until the replication analysis-completeness gate passes. Use current web search to compare AI video platforms only when generation is required, and use lawful web-sourced footage only when the user has not supplied adequate material.
Before loading or downloading a model for media analysis, read references/local-model-routing.md. Inventory the repository's existing local and pinned mirrored capabilities, choose the minimum model chain needed for the evidence gap, run inference locally without driving the visible editor UI, and record exact model/runtime/fallback provenance. Never load every available model by default or create a duplicate cache.
When the user needs web-sourced footage or asks where downloadable material can be found, read references/web-footage-sourcing.md. Give current, task-specific platform suggestions from live search and rank them by source legitimacy, explicit download support, usage rights, visual fit, quality, and provenance. Keep the skill provider-neutral; never hard-code one platform or brand as the permanent route.
For every completed automatic edit, read references/professional-editing-workflow.md. Analyze images directly; analyze video with representative frames, speech/OCR, semantics, and global plus subject-region optical flow. Stabilize before tracking or enhancement. Ask about image-to-video or image-to-image models only after inspection proves that generation is materially useful.
When a video plan could benefit from temporal emphasis, shot-matched color shaping, foreground/background separation, a product or person hero treatment, an editable subject outline, or identity replacement, read references/curves-and-subject-effects.md. Consider these capabilities during shot design instead of waiting for the user to name a control. Analyze in source time before retiming, use speed curves only for motivated timing changes, use Color Wheels to preserve skin and product identity while shaping the look, derive cutouts and outlines from verified masks, require explicit authorization for face swap, and validate preview/export parity and temporal stability before delivery.
When remote generation is materially required, read references/remote-video-generation.md. Search current official documentation, compare only providers that fit the shot blueprint, obtain approval before any paid or privacy-sensitive job, normalize the asynchronous task and provenance, download expiring output bytes, and add verified results to My assets without automatic timeline placement.
For product, brand, marketing-commerce, website-promotion, or other promotional edits, read references/promotion-narrative-workflow.md. Proactively construct an ambitious evidence-backed umbrella narrative rather than a feature list or kinetic-typography montage. Unless the user explicitly requests a teaser, build a complete problem-to-transformation-to-proof-to-CTA arc and actively find several visually distinct cases—normally at least three—each with its own setup, product action, visible result, and connection to the final payoff. Never invent customers, outcomes, metrics, or product behavior to make the story feel larger.
For highlight edits and reference replications where emphasis or dramatic impact matters, read references/highlight-tension-workflow.md. Treat saliency as candidate evidence, assign setup/rise/pre-impact/peak/aftershock roles, design a non-flat tension envelope, protect the decisive hero frame, and reject completion when accurate cutting still lacks a dominant payoff.
For a website walkthrough or promotional recording, use a supported browser-control skill to inspect and rehearse the authorized journey before capture. Read that browser skill completely before browser actions, then follow references/website-promo-workflow.md. Build and complete a page/flow coverage manifest before drawing product conclusions. When required pages are gated, ask the user to sign in themselves in the selected browser; never request credentials or describe inaccessible behavior as verified. Confirm any consequential external action separately, protect signed-in and personal data, and never claim a real screen recording was captured when only screenshots or static assets were available.
Treat tutorial-demo, vlog-event, marketing-commerce, and narrative-documentary as narrated-by-default categories. Preserve and reuse authorized source speech when it already carries the required story; otherwise author the minimum complete narration needed for context, progression, visible result, consequence, and closure, then synthesize it before timing picture. Do not ask whether narration should exist unless the user explicitly requests a source-only, music-only, or silent treatment; ask only for choices that materially affect language, casting, claims, or delivery.
For narrated edits, read references/voiceover-workflow.md. Prefer Timeline Studio's owned, pinned browser-local voices for every supported language. Route Chinese and mixed Chinese/English narration through the owned Hojo TTS Light 80M browser bundle and cast one of its two stable built-in reference profiles—晴岚 / zh_f_qinglan or 若溪 / zh_f_ruoxi—for each narrator or character; never install or use Hojo 40M or MeloTTS for this route. Use a remote service, operating-system voice, or unowned runtime only when the requested language or voice is unavailable locally and the user explicitly approves that fallback. Unless the user requests anoth

ソースを見る ↗

ファイルのメタデータ

name: edit-timeline-studio
description: Analyze images, video, speech, motion, products, and websites; route local vision, audio, depth, tracking, matting, identity, and restoration models; auto-edit, replicate, enhance, caption, voice, assemble, annotate, validate, and export editable Timeline Studio projects and videos. Use for reference-video remakes, filter and repeated-shot reconstruction, subject-aware reframing, clip splitting, source-time speed curves, Color Wheels grading, ramps and holds, person or product cutout, person or object outline, authorized face swap, shot and timing reconstruction, timeline markers, chapters, beat cues, review notes and ranges, supplied or web-sourced footage, AI video platform selection, cleanup, highlights, product promotion, website walkthroughs, image-to-video assisted edits, optical-flow editing, depth/2.5D/transition finishing, AI voiceover, subtitles, short-form production, .timeline automation, or editor evaluation.

元のテキストを表示

---
name: edit-timeline-studio
description: Analyze images, video, speech, motion, products, and websites; route local vision, audio, depth, tracking, matting, identity, and restoration models; auto-edit, replicate, enhance, caption, voice, assemble, annotate, validate, and export editable Timeline Studio projects and videos. Use for reference-video remakes, filter and repeated-shot reconstruction, subject-aware reframing, clip splitting, source-time speed curves, Color Wheels grading, ramps and holds, person or product cutout, person or object outline, authorized face swap, shot and timing reconstruction, timeline markers, chapters, beat cues, review notes and ranges, supplied or web-sourced footage, AI video platform selection, cleanup, highlights, product promotion, website walkthroughs, image-to-video assisted edits, optical-flow editing, depth/2.5D/transition finishing, AI voiceover, subtitles, short-form production, .timeline automation, or editor evaluation.
---

# AI Video Editing with Timeline Studio

Turn the user's exact editorial request and media into reversible Timeline Studio edits. Keep the editable timeline as the source of truth; never replace it with an opaque one-shot render.

## Choose the execution path

1. On first local use after installation, read [references/host-environment.md](references/host-environment.md). If Node.js is unavailable, start with the zero-dependency Shell or PowerShell bootstrap; otherwise run `node scripts/setup-host.mjs --check`. Agent-driven Chinese and mixed Chinese/English voiceover uses Timeline Studio's owned browser-local Hojo TTS Light 80M two-voice bundle and does not require a separate Python voiceover capability. If language runtimes or dependencies are missing, show the exact installation plan and obtain explicit user approval before install mode; never treat Skill installation as permission to modify the host or download models.
2. Treat local project-file processing as the default for deterministic editing: inspect media locally, modify the portable `.timeline` through the command layer or local archive services, and render and verify decoded output when the task changes rendered media. Do not open a browser merely because the editor has a UI.
3. Treat `https://video-editor.ai-creator.top/` as the canonical hosted editor only when the user explicitly asks to use the website, provides no local repository or project path, or requires a hosted-only capability.
4. When this repository is available, prefer its Agent command layer and local media tools. Start the local server and browser only for a verified UI-only operation that the local project pipeline cannot express and the user has not required a local-only workflow. Read the actual server URL from process output; never assume port 5173.
5. Prefer the bundled Timeline Studio MCP tools when the host exposes them. Read [references/mcp-integration.md](references/mcp-integration.md), inspect the project, and always call `timeline_project_diff` before `timeline_project_apply` with the same revision and operations. The MCP server is a transport over the repository command runner, not a separate editing implementation.
6. When MCP is unavailable, inspect `package.json` for an Agent command script. Do not use `npm run ... --if-present` as capability detection because it can succeed silently. If the command runner exists, read [references/command-contract.md](references/command-contract.md), inspect the project, build a versioned plan, run the structural validator, and use `project.diff` as the authoritative semantic dry run before `project.run`.
7. If a required operation is missing from the local contract, state the exact gap. For repository-development work, implement the smallest shared local operation and renderer support before falling back to UI. Otherwise ask before switching to the browser workflow.
8. Do not claim deterministic or idempotent execution when only UI automation was available. State the limitation and preserve an editable project archive when the UI supports it.

## Workflow

For a marker-only request, read [references/timeline-markers.md](references/timeline-markers.md) and follow its inspect → plan → validate → diff → apply → inspect workflow through annotation handoff. Markers, chapter cues, ranges, and notes are project annotations; adding them requires no narration, model download, browser session, or video render. The media-production steps below apply only when the user also requests a media edit.

### 1. Inspect before editing

- Preserve the user's prompt verbatim as the creative brief.
- Resolve every referenced asset to an explicit path or URL. Never sweep a directory without approval.
- Inspect duration, dimensions, audio presence, and media type.
- Read the current project summary before changing an existing project.
- Before planning long videos, chapters, musical beat cues, review notes, or edit ranges, read [references/timeline-markers.md](references/timeline-markers.md). Inspect existing annotations and use evidence-backed markers to preserve editorial anchors and decisions where useful. Preserve user annotations and distinguish Agent observations from supplied feedback.
- Ask only when an unresolved choice materially changes the edit, such as the desired output duration or aspect ratio.
- For an automatic-editing request, read [references/auto-edit-workflow.md](references/auto-edit-workflow.md). Inspect first, classify the content, goal, and delivery with an explicit confidence level, then ask only the minimum category-specific questions that can change the cut. Never ask for facts discoverable from the media.
- For a request to reproduce, imitate, recreate, or reverse-engineer a reference video, read [references/replication-workflow.md](references/replication-workflow.md). Classify it as `editing-style replication`, `AI-generation replication`, or a hybrid; reconstruct filters, repetitions, source splits, speed curves, transitions, shots, and timing before building; and explicitly resolve whether the authorized original audio track must be retained. Do not start editing until the replication analysis-completeness gate passes. Use current web search to compare AI video platforms only when generation is required, and use lawful web-sourced footage only when the user has not supplied adequate material.
- Before loading or downloading a model for media analysis, read [references/local-model-routing.md](references/local-model-routing.md). Inventory the repository's existing local and pinned mirrored capabilities, choose the minimum model chain needed for the evidence gap, run inference locally without driving the visible editor UI, and record exact model/runtime/fallback provenance. Never load every available model by default or create a duplicate cache.
- When the user needs web-sourced footage or asks where downloadable material can be found, read [references/web-footage-sourcing.md](references/web-footage-sourcing.md). Give current, task-specific platform suggestions from live search and rank them by source legitimacy, explicit download support, usage rights, visual fit, quality, and provenance. Keep the skill provider-neutral; never hard-code one platform or brand as the permanent route.
- For every completed automatic edit, read [references/professional-editing-workflow.md](references/professional-editing-workflow.md). Analyze images directly; analyze video with representative frames, speech/OCR, semantics, and global plus subject-region optical flow. Stabilize before tracking or enhancement. Ask about image-to-video or image-to-image models only after inspection proves that generation is materially useful.
- When a video plan could benefit from temporal emphasis, shot-matched color shaping, foreground/background separation, a product or person hero treatment, an editable subject outline, or identity replacement, read [references/curves-and-subject-effects.md](references/curves-and-subject-effects.md). Consider these capabilities during shot design instead of waiting for the user to name a control. Analyze in source time before retiming, use speed curves only for motivated timing changes, use Color Wheels to preserve skin and product identity while shaping the look, derive cutouts and outlines from verified masks, require explicit authorization for face swap, and validate preview/export parity and temporal stability before delivery.
- When remote generation is materially required, read [references/remote-video-generation.md](references/remote-video-generation.md). Search current official documentation, compare only providers that fit the shot blueprint, obtain approval before any paid or privacy-sensitive job, normalize the asynchronous task and provenance, download expiring output bytes, and add verified results to My assets without automatic timeline placement.
- For product, brand, `marketing-commerce`, website-promotion, or other promotional edits, read [references/promotion-narrative-workflow.md](references/promotion-narrative-workflow.md). Proactively construct an ambitious evidence-backed umbrella narrative rather than a feature list or kinetic-typography montage. Unless the user explicitly requests a teaser, build a complete problem-to-transformation-to-proof-to-CTA arc and actively find several visually distinct cases—normally at least three—each with its own setup, product action, visible result, and connection to the final payoff. Never invent customers, outcomes, metrics, or product behavior to make the story feel larger.
- For highlight edits and reference replications where emphasis or dramatic impact matters, read [references/highlight-tension-workflow.md](references/highlight-tension-workflow.md). Treat saliency as candidate evidence, assign setup/rise/pre-impact/peak/aftershock roles, design a non-flat tension envelope, protect the decisive hero frame, and reject completion when accurate cutting still lacks a dominant payoff.
- For a website walkthrough or promotional recording, use a supported browser-control skill to inspect and rehearse the authorized journey before capture. Read that browser skill completely before browser actions, then follow [references/website-promo-workflow.md](references/website-promo-workflow.md). Build and complete a page/flow coverage manifest before drawing product conclusions. When required pages are gated, ask the user to sign in themselves in the selected browser; never request credentials or describe inaccessible behavior as verified. Confirm any consequential external action separately, protect signed-in and personal data, and never claim a real screen recording was captured when only screenshots or static assets were available.
- Treat `tutorial-demo`, `vlog-event`, `marketing-commerce`, and `narrative-documentary` as narrated-by-default categories. Preserve and reuse authorized source speech when it already carries the required story; otherwise author the minimum complete narration needed for context, progression, visible result, consequence, and closure, then synthesize it before timing picture. Do not ask whether narration should exist unless the user explicitly requests a source-only, music-only, or silent treatment; ask only for choices that materially affect language, casting, claims, or delivery.
- For narrated edits, read [references/voiceover-workflow.md](references/voiceover-workflow.md). Prefer Timeline Studio's owned, pinned browser-local voices for every supported language. Route Chinese and mixed Chinese/English narration through the owned Hojo TTS Light 80M browser bundle and cast one of its two stable built-in reference profiles—晴岚 / `zh_f_qinglan` or 若溪 / `zh_f_ruoxi`—for each narrator or character; never install or use Hojo 40M or MeloTTS for this route. Use a remote service, operating-system voice, or unowned runtime only when the requested language or voice is unavailable locally and the user explicitly approves that fallback. Unless the user requests anoth

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価格と実行コスト

Skill の入手: 価格未確認
実行: 実行要件は未確認です。Agent・API・サービス料金を提供元で確認してください。
ライセンス: MIT
価格未確認: 価格は未確認です。既存のソースとインストールリンクは利用できます。

無料で入手できても実行が無料とは限りません。価格は安全評価ではありません。価格情報を送る →

ソースの再確認が必要

ソースが変更されたか同期に失敗しました。インストール前に確認してください。

インストール前にレビュー: 自動インストールを避ける

ライセンス: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
The SKILL.md excerpt is truncated; full documentation may contain additional details but the provided content is sufficient for review.
The skill description is extremely broad, which might lead to overreach if not carefully scoped by the agent, but the workflow mitigates this.
This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

完全な監査を開く

ツール一覧はメタデータであり、互換性のテスト結果ではありません。プロンプトは提案です。

小さなタスクから始める

1ソースを読み、入力、出力、依存関係、権限を確認します。
2Agent に計画を求め、設定と費用を承認してから隔離環境でテストします。
3出力と変更ファイルを確認し、実行した結果だけを報告します。再現用にソースの版を保存します。

依存関係、API キー、外部サービスの料金をソースで確認してください。公開リポジトリでも全サービスが無料とは限りません。

出典と利用上の注意

登録済み

メタデータと審査情報は参考です。人気、ソースの発見、実行成功は別の事実です。

ソースリポジトリ: MartinDelophy/ai-video-editor
ライセンス: MIT
バージョン: 1.0.0
最終 GitHub プッシュ: 2026年9月8日
登録情報の更新日: 2026年9月17日
手順のパス: skills/edit-timeline-studio/SKILL.md @ b1c6b774865d

登録されたバージョンです。ソースのリリース情報を確認してください。

品質

73/100

強い

信頼

59/100

Do not auto-install

監査

75/100

高リスク

完全な監査を開く評価レポートを見る

Dependency or permission surface needs review
Permission surface may require sandboxing
Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
The SKILL.md excerpt is truncated; full documentation may contain additional details but the provided content is sufficient for review.
The skill description is extremely broad, which might lead to overreach if not carefully scoped by the agent, but the workflow mitigates this.
This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
成果: —

コピーはインストールではありません。件数は成功報告に基づき、品質全体を保証しません。

Agent 接続

Registry API 経由で判断、信頼、監査、ユースケース、インストールのシグナルを提供し、UI をスクレイピングせずに Agent が順位付けできます。

Install API を開く LLM テキスト形式 Manifest を開く自動解決プラン

詳細情報

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  "trust": {
    "score": 67,
    "label": "Manual review",
    "version": "trust-score-v4",
    "install_policy": "block",
    "evidence": {
      "stars": "792 GitHub stars",
      "repoActivity": "792 stars, 98 forks",
      "lastPushed": "1mo since push",
      "license": "MIT",
      "repository": "https://github.com/MartinDelophy/ai-video-editor/tree/main/skills/edit-timeline-studio",
      "install": "The tracked source changed or could not be synchronized. Review the current source before installing.",
      "installSafety": "standard package or runtime install path",
      "permissionSurface": "secrets or environment access, shell or command execution",
      "documentation": "Strong README/SKILL.md context",
      "agentOutcomes": "No agent outcome data yet"
    },
    "outcome_evidence": {
      "total": 0,
      "successes": 0,
      "failures": 0,
      "not_relevant": 0,
      "success_rate": null,
      "recent_success_rate": null,
      "recent_failure_rate": null,
      "install_attempts": 0,
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      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
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      "agent-skill"
    ],
    "known_risks": [
      "The SKILL.md excerpt is truncated; full documentation may contain additional details but the provided content is sufficient for review.",
      "This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
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      "successfulOutcomes": 0,
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      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
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      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 75,
    "risk_level": "risky",
    "risk_label": "Risky",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required",
      "The SKILL.md excerpt is truncated; full documentation may contain additional details but the provided content is sufficient for review.",
      "The skill description is extremely broad, which might lead to overreach if not carefully scoped by the agent, but the workflow mitigates this.",
      "This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution"
    ]
  },
  "safety_gate": {
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    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 73,
    "label": "Strong"
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  "supply": {
    "track": "Research and knowledge work",
    "scenario": "Research agents",
    "maintenance": "1mo since push",
    "risk": "Risky"
  },
  "alternative_skills": [
    {
      "slug": "latent-spaces-brag-slim",
      "name": "brag-slim",
      "url": "https://www.openagentskill.com/skills/latent-spaces-brag-slim",
      "stars": 13807,
      "install_command": "npx skills add latent-spaces/brag --skill brag-slim",
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      "audit_score": 84
    },
    {
      "slug": "orchestra-research-nemo-curator",
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      "install_command": "npx skills add Orchestra-Research/AI-Research-SKILLs --skill nemo-curator",
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      "audit_score": 85
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    {
      "slug": "krillinai-krillinai-render-horizontal",
      "name": "krillinai-render-horizontal",
      "url": "https://www.openagentskill.com/skills/krillinai-krillinai-render-horizontal",
      "stars": 12690,
      "install_command": "npx skills add krillinai/OpenCreator --skill krillinai-render-horizontal",
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      "audit_score": 85
    },
    {
      "slug": "openclaw-openai-whisper",
      "name": "openai-whisper",
      "url": "https://www.openagentskill.com/skills/openclaw-openai-whisper",
      "stars": 391309,
      "install_command": "npx skills add openclaw/openclaw --skill openai-whisper",
      "trust_score": 81,
      "audit_score": 86
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  ],
  "do_not_use_when": [
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    "production agents without a repository review",
    "The SKILL.md excerpt is truncated; full documentation may contain additional details but the provided content is sufficient for review.",
    "Audit risk risky exceeds max_risk=medium",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required"
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  "agent_contract": {
    "task_input": "Use edit-timeline-studio in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 67/100 Manual review",
      "Audit: 75/100 Risky",
      "Safety: 31/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "martindelophy-edit-timeline-studio (edit-timeline-studio)",
      "install_command": "",
      "risk_summary": "Risky; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
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  },
  "outcome_feedback": {
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    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "martindelophy-edit-timeline-studio",
      "task": "Use edit-timeline-studio in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
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      "task_success": true,
      "output_quality": 4,
      "error_type": null,
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      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
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  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/martindelophy-edit-timeline-studio",
    "api": "https://www.openagentskill.com/api/agent/skills/martindelophy-edit-timeline-studio",
    "audit": "https://www.openagentskill.com/skills/martindelophy-edit-timeline-studio/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=martindelophy-edit-timeline-studio&task=Use%20edit-timeline-studio%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20edit-timeline-studio%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20edit-timeline-studio%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/martindelophy-edit-timeline-studio/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/martindelophy-edit-timeline-studio"
  }
}

クリエイター向け

掲載元

Registry により登録

申請可能

この掲載は公開ソースから登録されており、メンテナー申請が承認されるまで公式として表示されません。

作成者: MartinDelophy
ソース: MartinDelophy/ai-video-editor
インデックス作成者: OpenAgentSkill コミュニティインデックス

帰属は公開リポジトリまたは作成者プロフィールにリンクされています。作成者は掲載を申請して所有権シグナルを更新できます。

このスキルを申請

所有者の申請

このスキル掲載を申請

この Registry により登録掲載は MartinDelophy に帰属していますが、まだ公式として表示されていません。申請すると、確認済み所有者シグナルが追加され、今後の公開、インストール、監査更新の信頼性が高まります。

共有キット

クリエイター被リンクキット

README にエビデンスバッジを追加

開発者がリポジトリを評価する場所で、正規掲載、現在の信頼・監査シグナル、実際の Agent-Proven エビデンスを表示します。

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/martindelophy-edit-timeline-studio?metric=listed&label=Listed)](https://www.openagentskill.com/skills/martindelophy-edit-timeline-studio?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/martindelophy-edit-timeline-studio?metric=trust&label=Trust)](https://www.openagentskill.com/skills/martindelophy-edit-timeline-studio?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/martindelophy-edit-timeline-studio?metric=audit&label=Audit)](https://www.openagentskill.com/skills/martindelophy-edit-timeline-studio/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/martindelophy-edit-timeline-studio?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/martindelophy-edit-timeline-studio?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

バッジをプレビュー監査を開くクリエイターキット

コミュニティシグナル

このスキルが Agent ワークフローに役立つかを共有してください。集約されたフィードバックがランキングを改善します。

概要