agentleFS
Galbaz1Galbaz1/video-research-mcp/skills/video-production/SKILL.md

video-production

Skill23 starsChanged 40 days agoMITView on GitHub

Assemble multi-clip AI video projects with reference assets, continuity checks, frame and audio QA, and montage assembly. Use for complete video production, not video analysis or isolated provider settings.

23 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use email-marketing, backend-development and 9 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • claude-office-skillsSkill

    email-marketing

    Email marketing automation - campaign creation, sequence building, A/B testing, deliverability optimization, and analytics

    Also in 3 projects that use this

  • mrgoonieSkill

    backend-development

    Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.

    Also in 3 projects that use this

  • nilssonrSkill

    seo

    Full SEO workflow for auditing pages and creating SEO-optimized content. Provides checklists with educational explanations aligned with Google Search Central documentation.

    Also in 3 projects that use this

  • SupabaseSkill

    copywriting

    Write or audit UI copy (buttons, labels, empty states, error messages, tooltips, form text) anywhere in the monorepo. Load it before shipping or reviewing any user-facing text — including when copy is incidental to the task, like a new feature that adds buttons, toasts, dialogs, or validation messages.

    Also in 3 projects that use this

  • AnthropicSkill

    design-system

    Audit, document, or extend your design system. Use when checking for naming inconsistencies or hardcoded values across components, writing documentation for a component's variants, states, and accessibility notes, or designing a new pattern that fits the existing system.

    Also in 3 projects that use this

  • Microsoft AzureSkill

    design

    Design rules and conventions for the API Center Portal. Use when editing detail pages, card components, badges, layout, navigation, sidebars, or headers. Covers badge styling, metadata placement, page navigation patterns, and layout alignment.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

2 rules. 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 20 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use a bounded production loop: brief → assets → draft → inspect → repair → assemble → verify.

    line 8
  2. Distinctive:

    When the creative approach is open, use creative-concept-design to choose a treatment and inspect a narration audition and representative …

    line 12

“Common” is measured: kept by at least 6 in 10 of the 20 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Video Production

Use a bounded production loop: brief → assets → draft → inspect → repair → assemble → verify. This skill supplies the workflow; discover actual generation, image, audio, and filesystem tools before execution. Read video-generation for current provider capabilities and ffmpeg-production for encoding recipes.

1. Brief and Assets

When the creative approach is open, use creative-concept-design to choose a treatment and inspect a narration audition and representative animatic before full production.

Record audience, message, shot list, duration, format, audio, delivery destination, and acceptance criteria. Audit existing footage and supplied images before generating replacements. Keep source assets unchanged. For paid generation, fix the spend limit, maximum attempts, and worker concurrency before starting.

Completion: each shot has a source or supported generation path, and each parallel worker owns a distinct output directory.

2. Visual Continuity

When multiple shots share a subject or setting, choose one inspected reference image per visual world. Store it with the prompt and a short identity/lighting descriptor. Use the selected provider's real reference mechanism; character/style consistency is a QA goal, not a promised connector parameter.

Choose one pattern, then read only its section in workflow-patterns.md:

NeedPattern
Distinct scenes sharing assetsAnimate and propagate
Continuous motionFrame-forward chain
Compare moods or treatmentsParallel variants
Longer continuous takeExtension, if the provider supports the input

Completion: references fit the selected input mode and required features are visible in the inspected assets.

3. Draft and Inspect

Generate one draft per shot within the agreed budget. For parallel shots, join all required workers before assembly. Retain operation IDs and poll pending jobs; do not duplicate a job because a client timed out.

Probe each returned video and inspect a contact sheet, playback, and audio. Check composition, identity, lighting, text, object permanence, motion, internal cuts, pronunciation, and sync. Sampling at 1 or 10 fps is a diagnostic aid; it does not prove every frame or audio sample is correct.

Completion: every shot has a recorded pass/fail decision and evidence against its acceptance criteria. A failed, refused, empty, or missing output remains part of the record.

4. Targeted Repair

For a measured defect, change one variable and allow one repair attempt per shot within the remaining budget. Preserve both outputs and explain the selection. Stop if the same infrastructure failure repeats, the provider refuses, or the budget is exhausted. Simplify the shot or deliver the accepted subset with explicit omissions; never imply a partial film is finished.

Completion: every retained shot passes, or the unresolved shot is named with its smallest next intervention.

5. Assemble and Verify

Normalize retained clips to compatible frame rate, dimensions, pixel format, timebase, and timestamps before concat/xfade. Use only necessary denoise/sharpen/grade operations; compare against the source so processing does not hide or introduce defects. Apply grain after denoise and interpolation if desired.

Measure actual durations to compute transition offsets. If clips carry audio, pair video overlap with the intended audio transition; silent clips or a separate soundtrack need a different mapping. See the reference for FFmpeg commands.

Probe the final file and watch/listen through every transition and the ending. Confirm duration, dimensions, fps, audio, readability, source attribution, and all required shots. Return the playable local path and inspection evidence. Keep preview, verified local final, and published distinct; publication requires the authorized destination.

Completion: the delivered artifact exists, is playable, and satisfies the recorded brief, or unresolved criteria are explicitly reported.

Related Skills

  • image-generation: reference prompts and edits.
  • video-generation: current provider constraints and clip requests.
  • tts-production: narration and alignment.
  • ffmpeg-production: audio/video processing and export presets.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.