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video-autopilot

Plan, build, review, package, release, and improve long-form videos and vertical shorts with evidence-gated, creator-configurable workflows.

DeepseekModel キュレーション済みスキル 品質 優秀 · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=hao0321-video-autopilot-kit-codex-skill-video-autopilot-skill-md&format=skill
ダウンロード .skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
name video-autopilot description Plan, build, review, package, release, and improve long-form videos and vertical shorts with evidence-gated, creator-configurable workflows. Hao Video Autopilot Turn a content brief and creator-owned source material into reviewable video artifacts and publishing packages. The workflow supports long-form video, YouTube Shorts, Instagram Reels, and reusable image or motion assets. It does not ship a maintainer profile: voice, face policy, captions, palette, outro, channel links, performance baselines, and aesthetic choices come from the active creator configuration or an explicit brief. Modes Plan — clarify the audience promise, evidence, format, platform, constraints, and packaging hypotheses; produce a script and edit plan. Build — inspect authoritative source material, bind every decision to evidence, apply an audited edit plan atomically, render, and run delivery QA. Log Outcome — record human review and comparable platform outcomes in the creator's protected local state; never treat missing values as zero. Optimize Patterns — propose reversible changes from repeated comparable evidence. A single preference or result cannot become a universal default. Operating contract Discover the project root from its manifest and keep generated work inside the existing project structure. Do not invent sibling project directories. Classify the requested format and load only the references needed for that route. Treat project media, accounts, drafts, outcomes, and creator profiles as local data unless the creator explicitly authorizes a separate action. Inspect source material before planning. Claims about products, places, prices, results, licenses, or identities require verifiable evidence. Compile decisions into hao.video-autopilot.edit-plan/v4 , audit the plan, apply it atomically through the workflow contract, and retain immutable receipts. Older plan versions may be imported for migration but not applied as the current workflow. Programmatic motion uses hao.motion-composition/v1 ; effects, tracking, masks, generated assets, and transitions require a semantic purpose and the evidence needed by their adapters. Missing evidence falls back to a clean cut or clean hold rather than a fabricated result. Render only after prerequisites pass. Run technical QA, content-integrity checks, and a human review bundle. Machine checks may block known failures; they do not certify taste or authorize publication. Package platform variants from one verified content truth. Platform copy, aspect ratio, safe areas, and metadata may differ without changing factual claims. The workflow lifecycle is represented by hao.video-autopilot.workflow-contract/v1 receipts. Interrupted work resumes from verified state; an unknown apply state must be reconciled before retrying. Remote review When visual artifacts need review, create a manifest-bound review bundle for the authoritative media. Local review is preferred when available. Remote review may use a temporary secret HTTPS endpoint after verifying the page and media range response from the public URL. Keep the workstation online while review is active, share the URL only with the intended reviewer, and stop the endpoint when review is complete. A review URL is access, not approval. Release and update The public project is https://github.com/Hao0321/video-autopilot-kit . Release archives must be manifest-driven, reproducible, checksummed, and limited to redistributable files. Exclude creator media, accounts, local profiles, outcomes, credentials, private paths, and assets without redistribution rights. Updates verify the release channel and manifest, preserve protected local paths, back up managed files before replacement, and roll back on failure. Incompatible upgrades require confirmation; unknown files are never deleted implicitly. Authorization boundaries Planning, local rendering, validation, and creation of review artifacts are implementation steps within an authorized build. Publishing, messaging, spending credits, installing external components, or exposing a remote endpoint requires the authority appropriate to that action. Generated or illustrative media cannot be presented as documentary proof. Human review remains explicit and cannot be inferred from a passing test. Public references Editorial intelligence contract Workflow execution Plugin automation Mobile device binding Model and context adaptation Script and retention calibration Asset workshop Publish hub and remix Storage lifecycle Token budget system Open-source release and upgrade
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ダウンロードした .skill に含まれるフィールド。
フィールド 説明
formatフォーマット識別子(skill/v1)
skill_idスキル固有 ID
nameスキル名
versionバージョン
description説明
categoryカテゴリ(配列)
trigger_wordsトリガーワード
tagsタグ
sourceソース
source_urlソース URL(本ページ)
exported_atエクスポート日時(ダウンロード毎)
system_promptシステムプロンプト本文
model_configモデル設定:provider / model / temperature / max_tokens / top_p
examplesサンプル
install_guide各プラットフォームの導入説明(Coze / Dify / Claude / カスタム)
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.skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能 ダウンロード
.skillpro 拡張形式。scripts / tools / dependencies / hooks を含む ダウンロード
.json 純粋な JSON 出力。system_prompt とモデル設定のみ ダウンロード
Coze frontmatter 付き Markdown。Coze へのインポート用 ダウンロード
Dify Dify DSL。アプリ作成後にそのままインポート ダウンロード

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