Skills Plugins MCP Prompt Model 博客 我的中心

embedded-captions

Add captions or subtitles to an existing single-subject talking-head video without editing the footage. Use for plain verbatim captions, cinematic captions embedded behind the subject, VFX captions, “炸/特效/酷炫字幕,” or a named identity from the 35-style catalog. Route by visual identity, not by backend engine. The quiet `anchor` rail is the default; embed every word only when the user explicitly wants a fully cinematic treatment. The workflow runs locally end to end, including transcription and subject matting; split multi-shot footage before applying it.

DeepseekModel Curated skill Quality Excellent · 90 v1.0.0

Get

https://deepseekmodel.com/api/download.php?id=heygen-com-hyperframes-skills-embedded-captions-skill-md&format=skill
Download .skill Standard format with system_prompt and model_config, ready for any agent framework
The actual content of the system_prompt field in the .skill file.
name embedded-captions description Add captions or subtitles to an existing single-subject talking-head video without editing the footage. Use for plain verbatim captions, cinematic captions embedded behind the subject, VFX captions, “炸/特效/酷炫字幕,” or a named identity from the 35-style catalog. Route by visual identity, not by backend engine. The quiet `anchor` rail is the default; embed every word only when the user explicitly wants a fully cinematic treatment. The workflow runs locally end to end, including transcription and subject matting; split multi-shot footage before applying it. First, keep this skill fresh — confirm with the user before running: npx hyperframes skills update embedded-captions . A fast no-op when everything is current; otherwise it refreshes this skill plus the core domain skills it depends on before you rely on them. Embedded Captions One catalog, picked up front ( CATALOG.md — 35 identities; the engines behind it are backend detail). Standard (default) builds a clean verbatim rail (lower-third subtitle carrying most text) + an embed climax composited into the scene behind the subject at the peak. Cinematic is pure embed — no rail, every caption composited behind the subject (hero typography, accumulation, occlusion as the effect). Theme is a complete themed constitution — body paradigm × hero setpiece × front fx × plate reaction, composed from registries ( themes/README.md ): ordnance terminal neonsign stardust stomp . Most explainer / voiceover is Standard ; embed is the scarce, earned peak — embedding every word is the common mistake; Theme is for VFX-grade asks ("炸", "特效", "像 AE 做的"). Operational flow (TL;DR) Routed through /hyperframes , the intent layer confirms only the input (which clip) and announces the identity pick as a deferred ask — the shortlist needs the probed clip, so it stays at step 1 below; the layer's run-shape questions don't apply (the footage is untouched, there is no storyboard to review). A BRIEF.md , when present, carries the confirmed input and any user notes — read it first. The craft prose below is long; the pipeline itself is short — and everything deterministic is computed or compiled, never hand-written: Decision gate (refuse bad clips) → pick ONE identity from CATALOG.md (35 identities; engine/compiler derived by lookup — never surface a mode/category question) hyperframes init (skip it if the project dir already exists with the video inside — matte.cjs / transcribe.cjs adopt any video in the dir as source.mp4) → bash scripts/prepare.sh <project> (matte ∥ transcribe ∥ audio-envelope in parallel, then safe-zones v2 with scene palette/optics/lighting — one command, nothing forgotten) author a small JSON of creative choices (read safe-zones.json first): Cinematic → plan.json → fill-timings.cjs → fit-fonts.cjs → make-composition.cjs ; Theme → theme.json → make-theme.cjs (rail/panel/poem/takeover paradigms; anchor is the quiet rail default) Visual QA : node scripts/preview-frames.cjs <project> → faithful composite previews in ~2s/frame (no render). Check § Visual QA before paying for a render. render-and-composite.sh → gates (timing / occlusion+hero / overflow / hand-off) → final.mp4 Load-bearing rules people miss: rail (default) + embed (promotion). drop (filler, not shown) / rail (verbatim lower-third subtitle, in front, carries most text) / embed (a peak word composited behind the subject). Standard mode does both , embedding only the peak(s). See § Caption model . The video is delivered UNTOUCHED (Standard/Cinematic; Theme mode's PLATE budget is the one sanctioned exception — register-gated reaction beats (charge-dim, punch, shake, grain) defined per theme DNA and applied AFTER the matte composite so subject+text+plate move as one frame) — captions are the only thing added; the matte just lets the subject occlude the embed track. Never grade/recolor/scanline the footage. Two rulebooks: rail → references/rail.md (thin), embed craft → references/composition-craft.md (rich, embed-only). Skim by need. Caption model — rail + embed Every spoken phrase is one of three things: What How it's shown drop filler — um/uh, stutters, self-corrections not shown rail the default — ordinary spoken content (verbatim) clean lower-third subtitle, in front , readable. A punch word can get an inline emphasis highlight (accent colour / active-word pop) — it stays on the rail. embed a promoted peak — the headline beat one big word composited behind the subject (matte occlusion), designed entrance + exit The rail carries most of the text; embed is the scarce, earned peak. Scarcity is per beat/block, not per clip : ≤1 hero per block (thought), never two co-visible, ≥ a beat of air between hero windows (the compiler warns under 0.6s). A short clip → usually 1–2; a long explainer → ~one per section. Among multiple heroes, the largest authored one is the APEX (it alone gets the full lockup embed + width-fit raise); smaller ones are MINOR peaks that ride their column as oversized emphasis lines (fg, damped motion) — not every beat needs the matte showcase, which is exactly what keeps the apex an event. Embedding every word is still the common mistake. Rail-surface identities build exactly this (rail = rail.html , embed = the climax in index.html ). Column-flow identities drop the rail and make everything embed-style — recommend them only for mood-over-verbatim asks, never for explainer / voiceover where the words must read (CATALOG.md encodes this per identity). Step 0 — pick ONE identity from the CATALOG One front-end, three engines behind. The user picks an IDENTITY from CATALOG.md (35 entries: 10 classic + 25 themed); the engine, compiler and authoring file are derived by lookup from the catalog row. Never surface "Standard vs Cinematic vs Theme" as a question — those are backend names (a product has one UX even with several engines). The catalog encodes everything routing needs: reading surface, voice, recommend-for, scene needs, adjacency notes for the genuinely-close pairs (loud↔ordnance, neon↔neonsign, cream↔stardust). The identity pick is a preference gate ( ../hyperframes-core/references/brief-contract.md § 1): in autonomous mode ("surprise me" / "decide for me"), pick from your shortlist yourself and state the one-line why instead of asking. Procedure: probe the clip → shortlist 2–3 identities from the catalog → recommend ONE with a one-line why → the user picks (autonomous mode: you pick, stating the why) → author that identity's file. Identities are engine-locked (no cross combos; opening one is a validation event — see dna/README.md). Always present your recommendation and let the user pick before you author. Don't silently default. (The full identity table lives in CATALOG.md — single source of truth for routing. The engine docs below describe each backend's authoring contract.) Recommendation heuristic : use the "Shortlisting heuristics" in CATALOG.md — they are identity-level (e.g. "炸" shortlists ordnance/stomp/terminal/loud and picks by WHAT should explode), never category-level. Unsure → anchor . Cinematic → write plan.json for a locked template, compiled by make-composition.cjs . Theme → read themes/README.md , author theme.json , run scripts/render-theme.sh (compiles + renders + plate reaction → final_fx.mp4 ). Decision gate — RUN FIRST Probe the video and classify the scene before either mode. ffprobe <video.mp4> # specs ffmpeg -ss <t> -i <video.mp4> -vframes 1 sample.png # at 20/50/80% Read the samples. Refuse if: Multiple speakers / hard cuts (split & render each shot, or refuse) No human subject (this skill is for talking-head) Under 3 seconds, no speech , or face never clearly visible — transcribe.cjs warns when audio is near-silent (Whisper hallucinates words like "Thank you." over silence); heed it and refuse rather than caption fabricated words Source already has burned-in captions / subtitles / heavy text graphics — adding a second caption system conflicts and the footage ships untouched (no covering/inpainting). Burned text often appears only mid-clip: sample a 1fps contact sheet ( ffmpeg -i in.mp4 -vf "fps=1,scale=160:-1,tile=10x5" sheet.png ), don't trust 3 spot frames. Transcript is garbage — non-native/heavy-accent speech can transcribe into confident gibberish. Sanity-read transcript.json before authoring; if it doesn't parse as language, try WHISPER_MODEL=medium once, else refuse (a verbatim rail of fabricated words is worse than no captions). Busy handheld with fast motion (matte flickers) Pre-flight probes (cost nothing, prevent the worst failures) Shot-cut probe. Sample frames at 20%, 50%, 80%. If a different subject/scene appears, trim the clip before the cut. Letterbox / pillarbox probe. Black bars on the first frame? Compute safe content rect and constrain caption placement inside it. Luminance probe. Sample the caption region's average luminance — under 60 → light text reads as-is, 60-180 → add the glyph scrim, 180+ → opaque text + scrim (never bare light text). Cinematic templates are cream+ screen and LOCKED — use this probe to pick a fitting identity (bright scenes → ink , or the opaque-rail anchor theme), never to recolour one. Identity recommendation by tone (you recommend; the user picks — see Step 0 + CATALOG.md). explainer / interview / must-read words → rail/panel-surface identities; poetic / social / "cinematic" → column-flow identities by register; "炸 / 特效 / VFX" / named worlds → themed identities. When unsure → anchor (words read, scene safe) — but present a shortlist and let the user choose. Pipeline — 5 steps 1. hyperframes init <project> --non-interactive --video <video.mp4> --skill=embedded-captions 2. bash scripts/prepare.sh <project> # matte ∥ transcribe (parallel) → safe-zones. One command. # → frames_fg/ transcript.json safe-zones.json 3. [AGENT STEP — the only creative step] author a small JSON; see below by mode Cinematic: author plan.json → node scripts/fill-timings.cjs → fit-fonts.cjs → make-composition.cjs Theme: author theme.json → bash scripts/render-theme.sh <project> (compiles + renders + plate fx) 4. node scripts/preview-frames.cjs <project> # ~2s/frame composite previews → § Visual QA (BEFORE the render) 5. bash scripts/render-and-composite.sh <project> # gates → final.mp4 + history/ snapshot (Theme mode: SKIP steps 3b/5 — render-theme.sh already runs compile + render-and-composite + _postfx.sh; the deliverable is final_fx.mp4, final.mp4 is pre-plate-reaction) Step 1's init checks the installed skills against the latest on GitHub and updates the global set if any are out of date. Step 3 differs by mode: Step 3 — Cinematic mode (pure embed) Read safe-zones.json first. Narration planes go in zones.hugLeft / hugRight — clean strips ABUTTING the silhouette (text far from the body reads as floating, not embedded; far corners are the fallback, not the default). The hero defaults to heroAnchor / heroBands.best (centered ON the subject, ~30–55% occluded). recommendation:"fg" moves NARRATION in front for legibility; the hero stays embedded whenever heroBands.feasible — hero-fg is the last resort. The DNA is the identity you picked in Step 0 (CATALOG.md) — do not re-open the choice here. Sanity-check it against the scene (bright hero band luma > 150 wants ink ; full pick guidance lives in the catalog, covering all ten incl. neon / glitch / chrome / velocity). State your pick + why; the user decides. The DNA locks type/palette/blend/motion + hero three-act; safe-zones v2 ( palette / optics / lighting ) parameterizes it to THIS scene automatically. Author <project>/cinematic.json — "dna": "<name>" + thought-BLOCKS, not raw groups: each block = lines of words (grouped 2–5 at clause boundaries) + the plane it stacks in + per-line css (size/weight/style only — no positions) + at most ONE line marked "hero": true (the promoted word; "text" for display form). Schema: scripts/make-cinematic.cjs header. Compile : node scripts/make-cinematic.cjs <project> — lowers blocks → plan.json → index.html. Generated for you: transcript-sequenced timings, accumulate-within-block, page-flip-between-blocks, the hero LOCKUP (a hero block's pre-context, HERO and post-context stack as ONE bonded composition centered on the subject — reading order top→bottom = spoken order by construction; context floats in FRONT while the hero embeds BEHIND = the depth sandwich; a mass rule keeps the hero dominating its context), apex/minor hero split, reading order by construction , fg fallback per safe-zones. Then the gates run as usual. (Hand-authoring plan.json directly remains possible for designs blocks can't express — then run fill-timings.cjs + fit-fonts.cjs + make-composition.cjs yourself.) Step 3 — Theme mode (themed constitution) Read themes/README.md FIRST — paradigm/setpiece registries, linkages, hard rules, and the exact theme.json schema. Pick a theme DNA by content register (each themes/<name>.json has voice + when ). State your pick + why; the user decides. Author <project>/theme.json — dna , lines (verbatim, transcript order; 1–5 words each — for takeover each line is one CARD), minors (emphasis words), hero:{match} (the climax word/phrase; leave it OUT of lines for embed setpieces, keep it IN for inline setpieces and panel+redact). Render : bash scripts/render-theme.sh <project> — compiles (verbatim-completeness gate at compile time), renders both layers, composites, applies the plate reaction → final_fx.mp4 . Use preview-frames.cjs between compile and render for Visual QA. Visual QA — preview BEFORE you render node scripts/preview-frames.cjs <project> [t…] composites faithful preview frames in ~2s each (caption layers screenshotted at seek-time + real video frame + matte occlusion + rail overlay = what the final composite will look like at that moment). Default samples = each group/climax window. A full render costs minutes — never use it to discover layout problems. Check the previews ( <project>/preview/sheet.png ) against this list — these are the failures the geometric gates cannot catch: Washout — light text over a bright region (window/sign/sky): unreadable → move the plane or change DNA/mode (bright scene → ink ). Text-on-text — captions over the scene's own text/graphics, or two caption groups colliding. Reading order — on-screen vertical order must match spoken order; the hero must not sit below later words. Hero presence — the climax should be BIG and visibly behind the subject (~30–55% occluded), not a floating label in a margin. Balance — one coherent column/band, not scattered fragments; margins breathing; nothing clipped. Then the 5 positive checks in references/reference-bar.md (poster test · timid test · one-glance hierarchy · scene handshake · dead-air audit) — the failure list keeps a render from being broken; the positive list is what makes it designed . Ship when both pass. Fresh-eyes review (recommended for anything user-facing): you have confirmation bias about your own layout. If you can spawn a subagent, give it ONLY the preview sheet + this checklist and ask for PASS/FIX verdicts per frame ("review these caption previews against the 5-point checklist; answer PASS or the specific fix per frame"). Apply fixes in plan.json / theme.json, recompile, re-preview — each loop costs seconds. Render once, when the previews pass. The DNA registry — ten visual languages (replaces the template catalog) Both modes draw from dna/ — ten art-directed visual languages that parameterize per scene (accent sampled from the footage, contact shadow along the measured light direction, depth-match blur, RMS-coupled hero amplitude): | DNA | Register | Scene fit | Voice |
Keywords that activate this skill. Click one to copy it.

This skill does not provide trigger words.

The downloaded .skill package contains the following fields.
Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

每日精选 Skill 推荐,免费送到你邮箱

输入邮箱,每天接收一个精选 AI Agent 技能推荐。完全免费,持续更新。

验证码 --

提交后我们会发送一封确认邮件,点击邮件里的链接才会开始收信。

完全免费,取消任意时间。我们不会发送垃圾邮件。