Omh Show Reel logo

Omh Show Reel

CommunityPopular
rlaope
omh-show-reel

[omh] Motion showcase to make: produce a source-grounded product film with audience-specific concepts, segment direction, authored motion, measured locale/export QA and reproducible source delivery. Use when the user says: show-reel, show reel, showreel, product showcase video, animated product film, motion showcase, animated portfolio, launch film.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-show-reel
Stars
3.6K
Forks
269
Bundled files
45
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.

  • 45 bundled files

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

  • Open source

    Published by rlaope on GitHub. Read the source before you install it.

Installation

Install the Omh Show Reel 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/rlaope/oh-my-hermes/tree/main/agent-skills/omh-show-reel
  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/rlaope/oh-my-hermes.git /tmp/oh-my-hermes
mkdir -p .claude/skills
cp -r /tmp/oh-my-hermes/agent-skills/omh-show-reel .claude/skills/omh-show-reel
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Show Reel 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 Omh Show Reel 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 Omh Show Reel 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.

Show Reel

This is an OMH show-reel workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).

Why This Exists

show-reel owns the complete motion-production method so factual claims, visual decisions, locale timing, revision budget, measured exports, and delivery receipts cannot drift apart. It does not render inside OMH core.

First Steps

  • Read references/brief-and-locales.md and references/storyboard-and-evidence.md before proposing visuals. Recover objective, audience, channel, duration, aspect ratio, fps, size cap, source/brand permissions, and tool availability from supplied context; honor explicit format and duration, ask only for irretrievable hard facts, and label reversible creative assumptions.
  • Resolve content language from current explicit user/audience/channel instructions, then applicable stable preferences, then user language. Keep reply_language under host persona and separate content_locale, onscreen_text, subtitle_text, pronunciation_text, voice_policy, font_policy, and direction_policy; never replace literal IDs, commands, URLs, or trademarks.
  • Compare at least 3 genuinely distinct concept candidates before selection; record the rubric, winner, rejected alternatives, and per-segment art direction. Read references/craft-workflow.md (the full upstream production method), toolkit/README.md under the loaded skill directory with a file reader, then references/renderer-adapter.md before choosing tools; a missing renderer means HOLD on a requested video, not a completed delivery.

Do Not Use When

  • Only a static infographic or summary card is needed; use omh-image-cards.
  • The request is a website, landing page or interactive UI build; use omh-frontend.
  • The output is a deck, PDF, spreadsheet or office document; use omh-materials-package.
  • Only a premium layout quality assessment is wanted; use omh-design-quality-gate.
  • The user already has rendered frames and needs a visual verdict, not new production; use omh-visual-qa.
  • Routine trimming, file conversion, live broadcasting, fishing equipment, tape storage, film criticism and social posting alone do not need this method.

Examples

Good example:

  • Prompt: Create a 20-second muted product showcase video for a Japanese audience using these approved screenshots and English brand names.
  • Expected behavior: Verify sources and locale, compare three concepts, direct segments, author motion with available tools, inspect the measured export, and deliver sources with honest gaps.
  • Why: An authored time-based showcase needs one coherent production method, not only an image prompt or critique.

Bad example:

  • Prompt: Convert this existing clip to a smaller MP4.
  • Expected behavior: Use a scoped media conversion tool; do not begin concept development.
  • Why: An existing file conversion is not an authored showcase.

Completion Checklist

  • Brief, source rights, selected concept and per-segment art direction exist; current explicit audience language beats stable preferences and user language, with reply and each content track kept separate.
  • Actual style frames, draft playback, keep/fix/rebuild, weakest-scene revision and delivery-size checks are observed or HOLD; codec/color/filesize, cuts, motion and locale QA are not inferred from file existence.
  • Requested video and source package are generated and transferred only when receipts exist; source package is reproducible and rights-cleared, and every missing evidence item remains named.

Recovery Notes

  • If sources, rights or irretrievable audience facts conflict, HOLD and ask one decision-changing question; label creative assumptions rather than interviewing for every aesthetic choice.
  • If font, renderer or voice capability is unavailable, return the useful storyboard and source handoff but keep the requested video HOLD; offer a subtitle-only or available-tool alternative without silently changing scope.
  • If revision budget is exhausted or export/transfer fails, keep the last observed partial state, exact defect and next repair; do not claim completion or retry an external mutation blindly.

When to Use

Use when a user needs an authored time-based product or work showcase, from evidence and audience framing to rendered motion, localized variants, export inspection, and source delivery.

Strong routing signals: `show-reel`, `show reel`, `showreel`, `product showcase video`, `animated product film`, `motion showcase`, `animated portfolio`, `launch film`, `product teaser video`, `製品ショーケース動画`, `제품 쇼케이스 영상`, `产品展示短片`

Catalog Metadata

Category: design Phase: motion-production Quality tier: evidence-gated Reasoning demand: standard

Quality bar:

  • Require at least 3 distinct concept candidates, per-segment art direction and source-grounded motion; never force a fixed palette, visual style, duration or audio track.
  • Use keep/fix/rebuild critique and a weakest-scene revision budget; reject repeated headline/card/rail grammar, require delivery-size moving evidence and both rebuilt cut boundaries. Technical metrics never fill independent artistic, playback or listening verdicts.
  • Read references/assets-and-rights.md, references/render-qa-delivery.md and references/source-package.md before export and delivery; missing required evidence keeps HOLD, never fabricated success.

Required inputs:

  • objective audience and channel
  • duration format and budget
  • source brand and asset permissions
  • available production tools

Expert clarification questions:

  • objective audience and channel
    • English: Who should watch this, on which channel, in which content language, and what should they understand or do?
    • Korean: 누가 어떤 채널에서 어떤 언어로 보고 무엇을 이해하거나 행동해야 하나요?

Expected outputs:

  • show_reel_brief/v1
  • show_reel_source_asset_register/v1
  • show_reel_concept_selection/v1
  • show_reel_storyboard/v1
  • show_reel_timing_map/v1
  • show_reel_renderer_handoff/v1
  • show_reel_preview_review/v1
  • show_reel_export_manifest/v1
  • show_reel_qa_report/v1
  • show_reel_delivery_manifest/v1

Artifact expectations:

  • Keep media, source files and authored text in the approved project folder; durable OMH records contain only bounded safe references, digests, states and gaps, never raw media, private source text or credentials.

Safety rules:

  • No automatic network/model/API calls, subprocess execution, dependency installation, font downloads, account discovery, voice cloning or paid defaults inside core; every chosen external action needs scope and authority.
  • A renderer unavailable, timeout, pageerror, missing font or partial export is HOLD or failed, never successful delivery. Never invent a tool receipt, translation, listening review or product capture.
  • Use user/official/rights-cleared assets first; generated visuals carry generation provenance and concept labels. Publish/spend/voice cloning requires separate explicit consent and exact-target approval.

Procedure: load references/procedure.md.

Runtime Evidence

Use the current host's own tools and subagent/task mechanism when available; otherwise run the same lanes sequentially or name the unavailable capability. A prepared plan, handoff, checklist, or skill installation is not execution, review, CI, merge-readiness, or merge evidence. Record actual tool results, or not_observed / not_available, in the record; never invent dispatch or host accounting. Treat supplied context as advisory, not proof of hidden memory reads or writes. State scope, constraints, verification, and the stop condition before work. Reply in the user's own words and the host's own voice: the host's persona owns reply language, tone, speech level, and sentence endings, progress updates included (where it sets no language, use the one the user wrote in), and OMH shapes structure and content only; OMH's record terms (surface, lane, wrapper, handoff, evidence boundary, not_observed) stay in records and tool calls, never in the sentence the user reads unless they ask about one; and when a real unresolved user decision or a useful briefing discussion remains, offer one specific, content-linked question. Completed work needs no question; omit unrelated non-action footers and generic offers to continue. Supporting paths are relative to this skill directory; sibling skill paths are relative to its parent. Resolve them from the host-provided skill base directory ({baseDir} on hosts that provide it), never a hardcoded install location. A named workflow not installed here is unavailable, not permission to emulate its host-specific capabilities. Verify through the real surface before done.

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 Omh Show Reel AI skill do?

[omh] Motion showcase to make: produce a source-grounded product film with audience-specific concepts, segment direction, authored motion, measured locale/export QA and reproducible source delivery. Use when the user says: show-reel, show reel, showreel, product showcase video, animated product film, motion showcase, animated portfolio, launch film.

Why use Omh Show Reel on TypingMind?

Because you install it once and use it with any model. Omh Show Reel 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 Omh Show Reel in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rlaope/oh-my-hermes/tree/main/agent-skills/omh-show-reel. 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 Omh Show Reel?

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 Omh Show Reel?

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

Is the Omh Show Reel AI skill free?

Yes. It is published on GitHub by rlaope 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇