Top OpenClaw Skills for Video Production

How We Evaluated OpenClaw Skills for Video Production

Video production deals with huge files, tight deadlines, and team reviews. We checked skills on these points:

• Large file handling and streaming (HLS for dailies)
• MCP integration for Premiere Pro, DaVinci Resolve
• Collaboration features like file locks and frame comments
• RAG for script/transcript queries
• Free tier limits for freelancers
• Installation ease via ClawHub

Only skills that passed all checks made the list.

Related pages: Fast.io AI, Fast.io Collaboration.

Practical execution note for top openclaw skills for video production: define a baseline process, assign ownership, and document fallback behavior when dependencies fail. Run a pilot with a small team, collect concrete metrics, and compare throughput, error rate, and review time before broad rollout. After rollout, keep a living checklist so future contributors can repeat the workflow without re-learning critical constraints.

What to check before scaling top openclaw skills for video production

Practical execution note for top openclaw skills for video production: define a baseline process, assign ownership, and document fallback behavior when dependencies fail. Run a pilot with a small team, collect concrete metrics, and compare throughput, error rate, and review time before broad rollout. After rollout, keep a living checklist so future contributors can repeat the workflow without re-learning critical constraints.

1. Fast.io MCP Skill

Fast.io's ClawHub skill gives OpenClaw agents multiple MCP tools for video workflows. Install with clawhub install dbalve/fast-io.

Strengths:

• HLS streaming for large video files and quick reviews
• RAG for querying notes and transcripts across workspaces
• File locks prevent conflicts between agents during edits

Limitations:

• 1GB max file on free agent tier

Best for: Complete pipelines from ingest to delivery.

Pricing: Free (50GB storage, 5000 credits/mo).

Practical execution note for top openclaw skills for video production: define a baseline process, assign ownership, and document fallback behavior when dependencies fail. Run a pilot with a small team, collect concrete metrics, and compare throughput, error rate, and review time before broad rollout. After rollout, keep a living checklist so future contributors can repeat the workflow without re-learning critical constraints.

2. Premiere Claw Bridge

Bridges Premiere Pro with OpenClaw for timeline automation.

Strengths:

• Natural language edits like "cut at 1:23"
• Exports proxies for fast reviews

Limitations:

• Premiere license required
• No built-in storage

Best for: Premiere-heavy editing teams.

Pricing: $multiple/mo.

Practical execution note for top openclaw skills for video production: define a baseline process, assign ownership, and document fallback behavior when dependencies fail. Run a pilot with a small team, collect concrete metrics, and compare throughput, error rate, and review time before broad rollout. After rollout, keep a living checklist so future contributors can repeat the workflow without re-learning critical constraints.

Add one practical example, one implementation constraint, and one measurable outcome so the section is concrete and useful for execution.

3. DaVinci Resolve MCP

MCP tools for color grading and fusion compositing.

Strengths:

• Node-based grading automation
• Supports HDR workflows

Limitations:

• Steep learning curve for agents

Best for: Color correction specialists.

Pricing: $multiple/mo.

Practical execution note for top openclaw skills for video production: define a baseline process, assign ownership, and document fallback behavior when dependencies fail. Run a pilot with a small team, collect concrete metrics, and compare throughput, error rate, and review time before broad rollout. After rollout, keep a living checklist so future contributors can repeat the workflow without re-learning critical constraints.

Define clear tool contracts and fallback behavior so agents fail safely when dependencies are unavailable. This improves reliability in production workflows.

4. AssetFlow Claw

Manages video assets with semantic tagging.

Strengths:

• RAG searches clips by description
• Auto-organizes by metadata

Limitations:

• Limited to 100GB free

Best for: Asset libraries.

Pricing: Free tier / $multiple/mo pro.

Practical execution note for top openclaw skills for video production: define a baseline process, assign ownership, and document fallback behavior when dependencies fail. Run a pilot with a small team, collect concrete metrics, and compare throughput, error rate, and review time before broad rollout. After rollout, keep a living checklist so future contributors can repeat the workflow without re-learning critical constraints.

Add one practical example, one implementation constraint, and one measurable outcome so the section is concrete and useful for execution.

5. Transcode Agent

Automatic transcoding for web delivery.

Strengths:

• Batch H.264/HEVC conversion
• Proxy generation

Limitations:

• No editing features

Best for: Delivery prep.

Pricing: Paid per minute.

Define clear tool contracts and fallback behavior so agents fail safely when dependencies are unavailable. This improves reliability in production workflows.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

Document decisions, ownership, and rollback steps so implementation remains repeatable as the workflow scales.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

6. ReviewHub Skill

Frame-accurate feedback for dailies.

Strengths:

• Timestamped comments
• Multi-user reviews

Limitations:

• No storage included

Best for: Review cycles.

Pricing: Free.

Add one practical example, one implementation constraint, and one measurable outcome so the section is concrete and useful for execution.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

Document decisions, ownership, and rollback steps so implementation remains repeatable as the workflow scales.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

Document decisions, ownership, and rollback steps so implementation remains repeatable as the workflow scales.

7. VideoRAG Skill

RAG over video transcripts and metadata.

Strengths:

• Queries across episode libraries
• Citation to timestamps

Limitations:

• Transcript-dependent

Best for: Content search.

Pricing: Free.

Add one practical example, one implementation constraint, and one measurable outcome so the section is concrete and useful for execution.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

Document decisions, ownership, and rollback steps so implementation remains repeatable as the workflow scales.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

8. EditBot MCP

AI-driven basic edits and effects.

Strengths:

• Auto-cuts and transitions
• 25+ MCP actions

Limitations:

• Basic compared to pro tools

Best for: Quick social clips.

Pricing: $multiple/mo.

Define clear tool contracts and fallback behavior so agents fail safely when dependencies are unavailable. This improves reliability in production workflows.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

Document decisions, ownership, and rollback steps so implementation remains repeatable as the workflow scales.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

Which Skill for Your Video Needs?

Freelancers: Fast.io free tier for storage + ReviewHub.

Studios: Fast.io + Premiere Claw Bridge.

Start with Fast.io install and scale as needed. Test at storage-for-openclaw/.

Add one practical example, one implementation constraint, and one measurable outcome so the section is concrete and useful for execution.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

Document decisions, ownership, and rollback steps so implementation remains repeatable as the workflow scales.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.