여러 업체와 공공기관의 사이버 보안 보고서를 검색하고 가져와 위협, 랜섬웨어, 침해 통계 등의 추세를 비교합니다. 분석에는 출처별 업체, 연도, 보고서를 표시하고 자료 간 차이도 따로 다룹니다.
- 분류별 위협 보고서를 찾을 때
- 특정 업체의 보고서를 가져올 때
- 여러 업체의 랜섬웨어 동향을 비교할 때
자료와 관점을 바탕으로 내레이션이 있는 영상 에세이를 만들거나, 게시물·아이디어·기능을 짧은 해설 영상으로 제작합니다. 블로그는 작성자의 녹음이나 음성 복제본으로 읽어 영상화하고, 결과를 검토한 뒤 받을 수 있습니다.
Turns content plus a stance into a video essay narrated by the DA, any post, idea or feature plus a length into a short DA-narrated explainer video, or the author's own audio reading of their blog post (a recording or their voice clone) into a finished video of that post, with scripted visuals rendered on HyperFrames, presence layer, rendered and read back. USE WHEN video essay, explainer video, short video about this post, N-minute video of my blog post, make a video about this, respond to this video, argue against this in a video, debate this, video response, DA video, narrated video, turn this essay into a video, react to this interview, make a video from my audio, I recorded myself reading the post, turn this post into a video, video from my voice clone, audio to video. NOT FOR the user's camera footage or clips (Video), audio-only podcast cuts (Video), one-off animation (HyperFrames).
실행 점수 미검증
설치 방법 보기VideoEssay는 자료를 바탕으로 내레이션이 있는 영상을 제작합니다. 영상 에세이 모드에서는 먼저 관점에 따른 주장을 글로 정리하고, 확인을 거친 뒤 영상 구성과 대본을 만들고 렌더링합니다. 특정 입장을 내세우지 않고 게시물, 아이디어, 기능을 지정된 길이의 짧은 해설 영상으로 만드는 것도 가능합니다. 다른 제작 방식으로 블로그 글을 작성자의 녹음, 작성자 음성 복제본 또는 DA의 낭독으로 영상화할 수 있습니다. 블로그 페이지와 낭독 중인 부분에 맞춘 영상을 함께 구성합니다. 완성된 영상은 내용과 화면을 검토한 뒤 받을 수 있습니다.
인터뷰나 영상에 대한 의견을 영상으로 전하거나, 기사나 기능을 짧게 소개할 때 사용할 수 있습니다. 블로그 내용에 맞춘 영상을 만들고 싶거나, 글을 직접 읽어 녹음한 음성을 영상에 넣고 싶을 때도 적합합니다.
처음 사용할 때 설정이 필요합니다. 음성 합성에는 Fish Audio를 사용합니다. 작성자의 음성 복제본을 쓰려면 관련 음성 ID와 API 키도 필요합니다. 이 스킬은 영상을 공개하지 않으며, 공개는 별도의 절차로 진행합니다.
이 소개문은 공개된 SKILL.md를 바탕으로 AI(OpenAI Codex)가 작성했습니다. 정확한 사양은 아래 원문을 확인하세요.
AI가 SKILL.md의 내용에서 주의가 필요한 작업과 도입 전제를 확인했습니다. 점수는 실제로 실행한 결과(실행 검증)만으로 매깁니다.
점수에는 넣지 않았습니다. 2026년 10월 28일 기준으로 AI(OpenAI Codex)가 판정했습니다. 참고용이므로 설치 전에 원문도 확인해 주세요.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Contents: Ideal State · Intent Routing · Tools · Data & Config · Quality loop · Gotchas · Examples
The DA's own video format, in two modes, each a fully automated production that proves itself before the user sees it. Essay mode argues first, then renders. Voice mode (run.json mode: "voice") turns the author's post, read by their recording, their voice clone or the DA reading their exact words (run.json narrator recorded | clone | da), into a video of the real post page scrolling with the spoken sentence highlighted, inserts directed from what the post argues (LIFEOS/TOOLS/VideoMeaning: MeaningMap, Direction, a two-vendor plan review), and the reader's portrait in the corner badge (the author's, or the DA's on a DA-read run).
Essay.md with verbatim, correctly attributed quotes reaches the user at the checkpoint (unless the ask skips it), and only then becomes Script.json and a render.Out/verify.json all green, and the frames and the Out/review/ studio pass read.~/Downloads/<slug>/ only through Deliver.ts, after a passing ArtDirection critique and Proof receipt on those exact bytes.Video.| Intent | Trigger | File |
|---|---|---|
| Argue | "write the argument", "essay first", "what's our take on this", the first step of every new run | Intents/Argue.md |
| Script | "script it", "turn the essay into beats", "plan the visuals" | Intents/Script.md |
| Produce | "produce it", "render the essay", "make the video from the script", re-renders after an edit | Intents/Produce.md |
| Full | "respond to this video", "video essay on this", "argue X in a video", raw content plus a stance to argue | Intents/Full.md |
| Voice | "make a video from my audio", "I recorded the post", "use my clone to read the post", a post plus a recording | Intents/Voice.md |
| Explainer | "make an explainer video", "a short video about this post / idea / feature", "a 2-minute video of my latest post", any source plus a length with no stance to argue | Intents/Explainer.md |
Full is Argue → review checkpoint → Script → Produce. The checkpoint after the essay is the default: text is cheap to change and a render is not. The user skips it by saying so in the ask ("straight through", "no review, just make it"). Voice has no essay and no DA-written narration; its narration rule, stages and inserts are in Intents/Voice.md. Explainer writes an Essay.md with kind: explainer (narration only, no opposing quotes) at the length asked for, then runs Script and Produce straight through; its optional YouTube leg (thumbnail on the post's header image, full description, private upload) runs through Video, never this skill.
| File | Read when |
|---|---|
References/ScriptSchema.md | writing or linting Script.json |
References/Style.md | composing frames, the thumbnail, or running DesignAudit (the house design system) |
References/Tools.md | running or debugging one stage tool directly, choosing a flag, or finding a run's files |
Setup.md | first run on a machine, any tool stops naming Setup.md, or a Config.json field's meaning or default |
Tools/Run.ts drives every run; the other stage tools, the run layout and the composition files are in References/Tools.md.
| Tool | Contract |
|---|---|
Tools/Run.ts --run <slug> [--from stage] [--to stage] [--force] [--music ambient|pulse] [--accept-review-shortfall] [--polish] | essay: lint, then narrate → score beside capture, then build, then verify beside thumbnail, then describe once verify passes (other stages wait only for what they read); after any failure no stage starts; voice: clean → align → plan → meaning → lint → capture → build → verify → describe |
Everything personal lives in the user zone. First-time setup is Setup.md, and bun skills/VideoEssay/Tools/Setup.ts --check reports what is still missing. With no config file every tool stops and names Setup.md.
LIFEOS/USER/CUSTOMIZATIONS/SKILLS/VideoEssay/Config.json: fonts (a missing face is an error, never a fallback), fontFamilies, avatar, runsRoot, blogBaseUrl, possessive, presenter, narrators.da, colors, badge, skipParagraphs and styleFile; each field's meaning and default is in the Setup.md field table, the face roles and colour keys in Setup.md § Faces and colours. Relative paths resolve against the config dir. Never change narrators.da.label for one run; pass --label at ingest instead.LIFEOS/USER/CUSTOMIZATIONS/SKILLS/VideoEssay/public/: created by Setup.ts and linked from Tools/public. It holds the avatar cut-out and staged runs, never the skill tree.LIFEOS/TOOLS/FishTTS.ts). The DA reads with its one voice, LIFEOS_CONFIG.toml [da.voices.main]: its fish_reference_id names the Fish voice and its fish_speed is the pace (no separate presenter voice since 2026-10-24). The author's clone uses [principal.voice] plus two env ids: FISH_PRINCIPAL_VOICE_ID, the Fish clone itself, and ELEVENLABS_PRINCIPAL_VOICE_ID, the id narration recognizes as a clone read. Key: FISH_API_KEY. Fish applies the pace itself, so no chunk is stretched afterward. Setup.md § LIFEOS_CONFIG.toml and § Accounts and secrets have the details.principal.name and the reader to the DA display name, both from LIFEOS_CONFIG.toml. A DA-read badge shows READ BY <READER> · <POSSESSIVE> AI (THEIR AI unless Config.json possessive says otherwise); a post the DA wrote itself (--label <DA NAME> at ingest) reads WRITTEN AND READ BY <READER>. Neither ever carries a voice-vendor logo or a clone credit.LIFEOS/USER/PRINCIPAL/PRONUNCIATIONS.json when present, plus a per-run pronunciations.json, applied to spoken text only.INTERCEPTOR_TEST_CONTEXT_ID in LIFEOS/USER/CUSTOMIZATIONS/SKILLS/Interceptor/preferences.env; Capture.ts stops naming that file when it is missing.Run.ts refuses a run dir under the config root or the user-data repo.Before the critique, every render passes the Assay video eval set (video-eval, skills/Assay/Tools/VideoEval.ts) in Run.ts's eval stage, as each intent's ## Evals section declares it; a blocking result fails the run.
Nothing this skill produces reaches the user as a first draft. The artifact goes through Skill("ArtDirection"): a direction council before new or large work, then the cross-vendor critique panel (skills/ArtDirection/Tools/Critique.ts) scores it against the rubric and names defects (for a run with a Meaning/Direction.rendered.json, pass --direction <run>/Meaning/Direction.rendered.json so each beat is also judged against its own rationale), then this skill iterates on those defects until the bar or reports the shortfall. Record the user's verdict with skills/ArtDirection/Tools/Calibrate.ts.
Hand-over is skills/ArtDirection/Tools/Deliver.ts. It refuses without a passing critique of those exact bytes and a passing Proof receipt (skills/Assay/Tools/Proof.ts run --artifact <file>), and it writes the delivery receipt the gate reads. Critique Out/essay.mp4 with --out <run> so Critique.json sits one level above it, then run Deliver.ts --artifact <run>/Out/essay.mp4 --critique <run>/Critique.json --to ~/Downloads/<slug>/. The thumbnail ships as the ≤ 2 MB q85 JPEG (Intents/Produce.md), critiqued and delivered the same way.
These change what a run does. Failures the tools already handle are documented at their fix sites in Tools/ (the Capture.ts header, Ingest.ts, Clean.ts, Narrate.ts, Build.ts, Page.ts, Verify.ts); read those when debugging that tool.
Tools/public must be the symlink into the USER store, never a real directory. A stray empty public/ dir (left behind by moving the store, for one) makes every Build and Setup fail on the publicDir invariant; delete it and let Setup.ts recreate the link.check fails on text layered under a chapter card (content_overlap) unless both card text blocks carry data-layout-allow-overlap; the attribute is not inherited.FishTTS.ts) on the model TTS_MODEL names (CROSS_VENDOR.fishVoice). Do not switch TTS_MODEL without re-probing that the new model still returns word timings; captions and beat timing depend on them.Capture.ts embeds the page's loaded faces and replaces post.png only once a marker pass proves the web fonts drew. DOM renders still miss ::before/::after content and mask-image icons (a nav's arrow glyphs, say). --pixel shows all of it, but through Capture.sh it is JPEG quality 50, which breaks the exact-colour marker pass (Capture.test.ts covers the fallback-face judgment).check measures text contrast (WCAG AA 4.5:1) and text overlap at sampled times, and refuses the render (white text on a mid-tone coloured header can fall under 4.5:1; a result wider than the space past its stop can overlap a lane label mid-build). Text colours come through readableOn() against the run's own ground, and DesignAudit measures at settle only, so run the seam check on the staged project when a render is refused; its raw JSON (hyperframes check <dir> --json) names the element, colours and time.Build.ts replaces the mp4's audio with exactly what the composition plays; voice renders fail Verify's −14 ± 1 LUFS if that replacement is skipped (Build.test.ts "delivered loudness").Capture.ts shoots each embed in a headless copy of the pinned browser and pastes the pixels in; loading markers must clear within 30 s or the capture fails, and it never writes a loading state. A link card taller than the reading band is never whole at reading zoom; show it with a screenshot insert of the post itself, selected by the card's own link.Example 1: respond to an interview
User: "Make a video essay answering this interview — I disagree with most of it: <youtube url>"
→ Full: Intake pulls the transcript; Argue writes Essay.md (quotes lint-verified, steelman, disagreement, argument), adversarial read, plus the optional writing audits when installed
→ checkpoint: the essay is shown; on "go", Script.json is written and linted
→ Produce: verify.json green, frames read; mp4 and thumbnail delivered through Deliver.ts and the description copied, all in ~/Downloads/<slug>/
Example 2: the DA reads a new post
User: "DA-read video of my new post on composting"
→ Voice: Ingest --narrator da; the post's own words narrated, its page scrolling with the spoken sentence highlighted, embeds and link cards as on the live page
→ meaning-directed inserts on the paragraphs they illustrate; verify.json green; critiqued and delivered to ~/Downloads/<slug>/
Example 3: edit one paragraph after review
User: "Change the ending — softer on the delete-everything advice"
→ Edit Essay.md and the affected beats in Script.json
→ Run.ts --from narrate: only the changed beats re-synthesize; captures stay cached; re-render, re-verify
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여러 업체와 공공기관의 사이버 보안 보고서를 검색하고 가져와 위협, 랜섬웨어, 침해 통계 등의 추세를 비교합니다. 분석에는 출처별 업체, 연도, 보고서를 표시하고 자료 간 차이도 따로 다룹니다.
기능이나 구성 요소 자체의 설계 요구와 시스템 전체의 목표를 세 단계로 비교합니다. 설계상의 충돌과 적절한 구현 범위를 정리하고, 제안한 설계가 전체 방향과 맞는지 평가합니다.
글의 주제에 맞는 격언과 인용문을 찾아 저자와 선정 이유를 함께 제안합니다. 출처가 있는 인용문을 추가하고, 사상가의 말을 주제별로 조사하며, 사용 기록을 관리해 같은 인용문을 반복하지 않도록 돕습니다.
블로그 삽화, 기술 도표, 비교 그림, 만화, 아이콘 등을 용도에 맞는 절차로 제작합니다. 구도와 색상, 이미지 모델을 정하고 검토용 이미지를 출력합니다.
브리프와 제작 기준에 따라 이미지, 영상, 슬라이드, 사이트 화면 캡처의 시각 품질을 평가합니다. 두 비전 심사자가 점수와 결함 우선순위를 제시하고, 정해진 횟수 안에서 수정을 돕습니다. 평가를 통과한 결과물만 전달할 수 있으며, 사람의 점수와 의견은 별도 기록해 심사 보정에 활용합니다.
주제, 연구 분야, 논문 ID로 arXiv 논문을 찾고 제목, 저자, 초록, 링크를 정리합니다. 새 논문을 확인하고, 제공되는 경우 AlphaXiv의 AI 생성 개요도 가져옵니다.