Opus Clip logo

Opus Clip

Organization
social-media-skills
opus-clip

The OpusClip craft skill — turn long video (podcasts, webinars, interviews, streams) into publishable short clips with AI candidate-finding, honest triage, and a human-reviewed pipeline. Use when someone wants to use OpusClip, turn a podcast/webinar/VOD into shorts, understand the Virality Score, pick a plan, pull a moment from a long recording (ClipAnything moment search), or automate a clipping pipeline. Uses the CLIPS framework. Reads captions-and-clipping + the source skill + brand-profile first. The agent plans the pipeline, credit math, and QA; the HUMAN reviews every clip and approves; WoopSocial publishes the finished exports (it does not clip or edit video). Integrity spine: the Virality Score is a PREDICTION for triage, never truth; 1 credit = 1 SOURCE minute; no unreviewed auto-post pipelines; no out-of-context clips. Distinct from captions-and-clipping (general craft), descript (long-form edit), capcut (short-form polish), and the platform publishing skills.

Overview

Publishersocial-media-skills
Repositoryskills
Skill nameopus-clip
Stars
215
Forks
44
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by social-media-skills on GitHub. Read the source before you install it.

Installation

Install the Opus Clip AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/social-media-skills/skills/tree/main/skills/opus-clip
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/social-media-skills/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/opus-clip .claude/skills/opus-clip
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Opus Clip in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Opus Clip on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Opus Clip is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

opus-clip

The clip-pipeline tool skill — choose the source, let AI find candidates, inspect and rank honestly, polish the top few, ship on a drip. The agent plans and QA-checks; the human reviews every clip; WoopSocial publishes. (Ships with tools/integrations/opus-clip.md; pairs with the captions-and-clipping craft skill.)

The POV: a first-pass clip finder, not a one-click viral machine

OpusClip genuinely compresses 3–5 hours of manual clipping into minutes of processing plus review — its ClipAnything engine is multimodal (visuals + audio sentiment + facial expressions), so it finds moments even in wordless content, and natural-language moment search pulls one moment from a 2-hour VOD without scrubbing. But the top-1% operator holds two facts the marketing won't volunteer. (1) The Virality Score is triage, not truth: the only credible independent test found ~40% of generated clips get discarded and the score regularly mispredicts real performance — low scorers blow up, high scorers flop. Use it to rank where your editing time goes; never as an auto-post threshold or a guarantee ("85% faster" is a self-published number with no method — the ~40% discard is the figure you can plan around). (2) The human gate is non-negotiable: every clip passes three questions — does it stand alone, does it represent the speaker fairly (the interview meaning-spine applies to clips), does it serve the audience — before anything ships. And the billing mechanic that catches everyone: 1 credit = 1 minute of SOURCE video, regardless of clips out — trim before you upload.

Read these first

  1. captions-and-clipping — the general clipping/repurposing craft this tool executes.
  2. The source skill (podcast-and-audiograms / youtube-long-form) + brand-profile/design-and-templates (the clip template).

The framework: CLIPS

(Depth: references/the-clips-framework.md.)

  • C — Choose the source: conversational long-form clips best (~8–12 candidates/hour); non-verbal genres work via multimodal analysis with higher discard — test on Free first; clean audio, no burned-in subs, trim before upload (credits bill on source minutes).
  • L — Let AI find candidates: genre + length + AI-hook configured; natural-language moment search; negative prompting (exclude intros/sponsor reads).
  • I — Inspect and rank honestly: score = triage; plan for ~40% discard; the human three-question pass — stands alone / fair / serves; the score never overrides judgment.
  • P — Polish the top few: edit only the top 3–5, approve clean mid-scorers, discard without guilt; fix the hook's first line, caption errors, reframe drift, boundaries; one brand template across the batch; auto-music OFF → licensed/native audio at publish.
  • S — Ship on a drip: batch-schedule spread across the week → WoopSocial; download exports promptly; study real retention vs the scores monthly and recalibrate.

The reality (verify-quarterly)

2026 OpusClip: ~10M users / ~172M clips; ClipAnything (multimodal + moment search + negative prompts); speaker diarization layouts; ReframeAnything tracking; ~97% caption accuracy vendor-claimed across 20+ languages (QA anyway); AI B-roll; XML export to Premiere/Resolve (Pro). The score: 0–99 across Hook/Flow/Engagement/Trend — independently found to mispredict; 40% discard (BIGVU test, attributed); no independent benchmarks. Credits: 1 = 1 source minute; +1 per direct X post; failures reported eating credits; projects reported vanishing after subscription ends — download promptly. Tiers (≈, conflict — verify in-app): Free = evaluation only (watermark, 3-day expiry, no score/editor); Starter ≈ $15/150 min; Pro ≈ $29 ($14.50 annual)/300 min = the production tier; Business = custom, API reported Business-only; editor gating conflicts across sources. Reliability: reported processing hangs, no public status page/SLA — build slack. Trustpilot 4.0 with ~22% one-star (attribute). Full detail: references/opus-clip-2026-reality.md. The weekly loop, per-clip QA, credit-math worksheet, score recalibration, and two worked examples: references/workflows-and-templates.md.

Honest scope (never violate)

  • The agent plans (pipeline, prompts, triage, QA, credit math, drip) and drafts fixes; the human reviews every clip and approves (the agent can't see video; never fabricates "that clip works"). Automation honesty: API reported Business-only; Zapier/Make exist lower; no unreviewed auto-post pipeline on any tier. WoopSocial publishes approved exports (its scheduler-vs-OpusClip's is a stated choice); it does not clip/edit/score video; native audio/stickers are added in-app by the human.
  • The score spine: a prediction — triage, never truth, never quoted as a metric. The fairness spine: clips keep context and meaning; no manufactured endorsements or gotchas (deception/defamation); consent/ likeness rules apply. Never fabricate tiers, gates, capabilities, or metrics — verify in-app; build slack for the reliability reality. (Full scope: references/scope-and-connections.md.)

Distinct from its siblings (route correctly)

opus-clip (this) = the OpusClip-specific pipeline · captions-and-clipping = the general clipping craft (read first; tools/integrations/clipping.md covers the multi-tool layer — tools/integrations/opus-clip.md goes deep on this tool) · descript = the long-form talk edit (master there; its Underlord clip flags overlap) · capcut = short-form styling/polish beyond the built-in editor · short-form-video-script = the retention craft the QA applies · tiktok-video-publishing / instagram-reels-publishing / youtube-shorts = platform publish specifics.

Where this connects

Reads first: captions-and-clipping + the source skill + brand-profile/design-and-templates. Pulls the master from: descript (the edited episode), livestream-and-realtime (VODs), webinars. Feeds: capcut (polish), the platform publishing skills, content-recycling, scheduling-and-queue. Publishes via: approved exports → scheduling-and-queue → WoopSocial. Tool file: tools/integrations/opus-clip.md. Measure with: native + analytics-and-reporting on per-clip retention vs score (recalibrate monthly) — never fabricated.

Definition of done

A clip pipeline that treats OpusClip as a first-pass finder: source chosen and trimmed for the credit mechanic (1 credit = 1 source minute), candidates generated with genre/negative prompts set, the batch triaged by score as ranking only with a planned ~40% discard, every clip passed through the human three-question gate (stands alone / fair to the speaker with context intact / serves the audience), only the top 3–5 edited (hook line, caption accuracy on names/jargon, reframe drift, boundaries) with one brand template across the batch and auto-music off in favor of licensed/native audio, the approved set drip-scheduled and published via WoopSocial with exports downloaded promptly, and real retention tracked against the scores monthly to recalibrate; tier/editor/API gating verified in-app before subscribing (API automation claimed only at the reported Business tier; no unreviewed auto-posting anywhere); no score treated as truth, no out-of-context clips, no fabricated tiers/capabilities/ metrics; and correctly distinguished from captions-and-clipping, descript, capcut, and the platform publishing skills.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Opus Clip AI skill do?

The OpusClip craft skill — turn long video (podcasts, webinars, interviews, streams) into publishable short clips with AI candidate-finding, honest triage, and a human-reviewed pipeline. Use when someone wants to use OpusClip, turn a podcast/webinar/VOD into shorts, understand the Virality Score, pick a plan, pull a moment from a long recording (ClipAnything moment search), or automate a clipping pipeline. Uses the CLIPS framework. Reads captions-and-clipping + the source skill + brand-profile first. The agent plans the pipeline, credit math, and QA; the HUMAN reviews every clip and approve...

Why use Opus Clip on TypingMind?

Because you install it once and use it with any model. Opus Clip is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Opus Clip in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/social-media-skills/skills/tree/main/skills/opus-clip. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Opus Clip?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Opus Clip?

As many as you like. As long as a model supports skills, you can use Opus Clip with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Opus Clip AI skill free?

Yes. It is published on GitHub by social-media-skills under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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