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VideoEssay

Turn a source and a point of view into a narrated video essay, or make a short explainer from a post, idea, or feature. It can also pair a blog post with its author’s recording or voice clone, then render and review the finished video.

OriginalShow the original description

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).

danielmiessler/LifeOS19,636 stars(GitHub 19,636 + cccskills 0)
Works withYouTube

Run score Not tested

See how to install

Good for

  • Making a video essay responding to an interview
  • Creating a short explainer about a post or feature
  • Turning a blog post and personal recording into video
  • Producing a narrated video from a voice clone

Overview

What it does

VideoEssay creates narrated videos from source material. For a video essay, it first develops a written argument based on a point of view, then prepares the visual structure and script, and renders the video after review. It can also make a short explainer of a specified length about a post, idea, or feature without taking a particular side. In another mode, it turns a blog post into a video using the author’s recording, a clone of the author’s voice, or DA narration. The video can combine the blog page with visuals timed to the spoken portions. You can review the content and visuals before receiving the finished video.

When it helps

Use it to present a response to an interview or video, introduce an article or feature in a short format, or turn a blog post into a video that follows its content. It also supports making a video from an author’s recording of their own post.

Example requests

  • “Make a video essay responding to this interview.”
  • “Turn the latest article into a two-minute explainer.”
  • “Make a video of this blog post using my recording.”

Notes

First-time use requires setup. Speech synthesis uses Fish Audio. Using a clone of the author’s voice also requires the related voice ID and API key. This skill does not publish videos; publishing is handled in a separate process.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Document check

AI checked the SKILL.md for operations that need care and for setup requirements. The score comes only from actually running the skill (hands-on test).

SafetyAre sending data, deleting files, and running commands disclosed?
AGoodRuns stop in review state; the skill does not upload or publish videos.
Easy setupDoes it need few tools or API keys, and are they documented?
BPartly lackingSetup, Fish Audio, and voice IDs and keys may be needed; details are in Setup.md.

Not counted in the score. Rated by AI (OpenAI Codex) as of Oct 28, 2026. Treat it as a guide and read the original before installing.

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Files included (43)

  • SKILL.md14.3 KB
  • Intents/Argue.md5.2 KB
  • Intents/Explainer.md7.3 KB
  • Intents/Full.md1.4 KB
  • Intents/Produce.md6.9 KB
  • Intents/Script.md3.8 KB
  • Intents/Voice.md10.1 KB
  • References/ScriptSchema.md4.3 KB
  • References/Style.md18.7 KB
  • References/Tools.md5.5 KB
  • Setup.md14.5 KB
  • Tools/.gitignore30 B
  • Tools/Align.ts6.6 KB
  • Tools/Build.ts20.8 KB
  • Tools/Capture.ts65.3 KB
  • Tools/Clean.ts21.7 KB
  • Tools/Compose.ts14.9 KB
  • Tools/CompositionTypes.ts5.5 KB
  • Tools/Describe.ts8.4 KB
  • Tools/DesignAudit.ts132.0 KB
  • Tools/DiagramLayout.ts29.0 KB
  • Tools/EssayLint.ts6.3 KB
  • Tools/Ingest.ts51.3 KB
  • Tools/Intake.ts3.4 KB
  • Tools/Lib.ts28.3 KB
  • Tools/Meaning.ts20.7 KB
  • Tools/Motion.ts12.1 KB
  • Tools/Narrate.ts24.4 KB
  • Tools/package.json418 B
  • Tools/Page.ts26.1 KB
  • Tools/PagePresence.ts31.8 KB
  • Tools/PageVisuals.ts88.9 KB
  • Tools/PlanBeats.ts4.0 KB
  • Tools/ReadCamera.ts11.2 KB
  • Tools/ReadSync.ts13.3 KB
  • Tools/Run.ts21.0 KB
  • Tools/Score.ts14.6 KB
  • Tools/ScriptLint.ts9.4 KB
  • Tools/Setup.ts11.1 KB
  • Tools/Theme.ts21.9 KB
  • Tools/Thumbnail.ts6.8 KB
  • Tools/tsconfig.json420 B
  • Tools/Verify.ts31.2 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

VideoEssay

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).

Ideal State

  • An essay run argues before it renders: a linted, steelmanned 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.
  • A voice run narrates only the author's own words, its page reads like the live post, and every page highlight and insert is timed to the paragraph being spoken.
  • Every render reads itself back before anyone sees it: Out/verify.json all green, and the frames and the Out/review/ studio pass read.
  • The mp4 and thumbnail reach ~/Downloads/<slug>/ only through Deliver.ts, after a passing ArtDirection critique and Proof receipt on those exact bytes.
  • Every run stops in review state; nothing uploads from this skill. Publishing is the user's separate call through Video.

Intent Routing

IntentTriggerFile
Argue"write the argument", "essay first", "what's our take on this", the first step of every new runIntents/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 editIntents/Produce.md
Full"respond to this video", "video essay on this", "argue X in a video", raw content plus a stance to argueIntents/Full.md
Voice"make a video from my audio", "I recorded the post", "use my clone to read the post", a post plus a recordingIntents/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 argueIntents/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.

FileRead when
References/ScriptSchema.mdwriting or linting Script.json
References/Style.mdcomposing frames, the thumbnail, or running DesignAudit (the house design system)
References/Tools.mdrunning or debugging one stage tool directly, choosing a flag, or finding a run's files
Setup.mdfirst run on a machine, any tool stops naming Setup.md, or a Config.json field's meaning or default

Tools

Tools/Run.ts drives every run; the other stage tools, the run layout and the composition files are in References/Tools.md.

ToolContract
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

Data & Config

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.
  • Voices: narration is synthesized on Fish Audio (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.
  • Names: the badge label defaults to the first word of 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.
  • Pronunciations (optional): LIFEOS/USER/PRINCIPAL/PRONUNCIATIONS.json when present, plus a per-run pronunciations.json, applied to spoken text only.
  • Capture (required for voice runs and capture inserts) drives the Interceptor test profile whose context id is 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.

Quality loop

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.

Gotchas

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.
  • Writing the skill's own files from a Bash heredoc trips the taint guard when the session has read outside content. Use the file tool for intent files in a session that has ingested a transcript.
  • HyperFrames 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.
  • Narration's word timings come from Fish Audio's timestamped speech (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.
  • Interceptor's default screenshot is a DOM render that draws every web font in Times. 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).
  • HyperFrames' own pre-render 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.
  • The rendered mp4 comes out quieter than the staged narration.wav, inside the HyperFrames render seam. 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").
  • Embedded frames (tweets, videos, widgets) never draw in the DOM-render capture, and never lay out in a hidden tab (they read "LOADING TWEET…" for the whole video). 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.

Examples

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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