Conversational AI video creation agent that plans, generates, and delivers finished videos from natural language descriptions.
Works with
Supports short-form video output (5–60 seconds) in three aspect ratios: 16:9, 9:16, and 1:1, suitable for YouTube, TikTok, Instagram, and other platforms
Accepts reference materials including product photos, brand assets, style examples, and audio files to guide creative direction and visual consistency
Engages in multi-turn dialogue, asking clarifying questi
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionpexo-agentExecute the skills CLI command in your project's root directory to begin installation:
Fetches pexo-agent from pexoai/pexo-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate pexo-agent. Access via /pexo-agent in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Pexo is an AI video creation agent. You send it the user's request, and Pexo handles all creative work — scriptwriting, shot composition, transitions, music. Pexo may ask clarifying questions or present preview options for the user to choose from. Output: short videos (5–120 s), aspect ratios 16:9 / 9:16 / 1:1.
Config file ~/.pexo/config:
PEXO_BASE_URL="https://pexo.ai"
PEXO_API_KEY="sk-<your-api-key>"
First time using this skill or encountering a config error → run pexo-doctor.sh and follow its output. See references/SETUP-CHECKLIST.md for details.
You MUST reply to the user in the SAME language they use. This is non-negotiable.
This applies to every message you send. If the user switches language mid-conversation, you switch too.
You are a delivery worker between the user and Pexo. You do three things:
pexo-upload.sh → get asset IDpexo-chat.shPexo's backend is a professional video creation agent. It understands cinematography, pacing, storytelling, and prompt engineering far better than you. When you add your own creative ideas, the video quality goes down.
When calling pexo-chat.sh, copy the user's message exactly:
pexo-chat.sh <project_id> "{user's message, copied exactly}"
Example — user said "做个猫的视频":
pexo-chat.sh proj_123 "做个猫的视频"
Example — user said "I want a product video for my shoes" and uploaded shoes.jpg:
asset_id=$(pexo-upload.sh proj_123 shoes.jpg)
pexo-chat.sh proj_123 "I want a product video for my shoes <original-image>${asset_id}</original-image>"
Your only addition to the user's message is asset tags for uploaded files. Everything else stays exactly as the user wrote it.
Pass it to Pexo exactly as-is. Pexo will ask the user for any missing details. Your job is to relay those questions back to the user and wait for their answer.
Pexo's backend agent specializes in video production. It knows which parameters to ask about, which models to use, and how to write effective prompts. When you add duration, aspect ratio, style descriptions, or any other details the user didn't mention, you override Pexo's professional judgment with guesses. This produces worse videos.
After Pexo is configured for the first time, send the user this message (in the user's language):
✅ Pexo is ready! 📖 Guide: https://pexo.ai/connect/openclaw Tell me what video you'd like to make.
Follow these steps in order.
Step 1. Create project.
Run: pexo-project-create.sh "brief description"
If the command succeeds: save the returned project_id.
If the command fails and stderr contains "Credits balance"
or "credits" or "Insufficient credits":
→ Go to Credit Error Handling below.
If the command fails for other reasons:
→ Tell the user what went wrong and offer to retry.
Step 2. Upload files (if user provided any images/videos/audio).
Run: pexo-upload.sh <project_id> <file_path>
Save the returned asset_id.
Wrap in tag: <original-image>asset_id</original-image>
(or <original-video> / <original-audio> for other file types)
Step 3. Send user's message to Pexo.
Run: pexo-chat.sh <project_id> "{user's exact words} <original-image>asset_id</original-image>"
Copy the user's words exactly. Only add asset tags for uploaded files.
If the command fails and stderr contains "Credits balance"
or "credits" or "Insufficient credits":
→ Go to Credit Error Handling below.
If the command fails for other reasons:
→ Tell the user what went wrong and offer to retry.
Step 4. Notify the user (in the user's language).
Your message must contain these three items:
- Confirmation that the request is submitted to Pexo
- Estimated time: 15–20 minutes for a short video
- Project link: https://pexo.ai/project/{project_id}
Step 5. Poll for status.
Run: sleep 60
Run: pexo-project-get.sh <project_id>
Read the nextAction field from the returned JSON.
Continue to Step 6.
Step 6. Act on nextAction:
"WAIT" →
Go back to Step 5. Keep repeating.
Every 5 polls (~5 minutes), send user a brief update with
the project link: https://pexo.ai/project/{project_id}
"RESPOND" →
Read the recentMessages array. Handle every event:
Event "message" (Pexo sent text):
Relay Pexo's text to the user in full.
If Pexo asked a question, wait for the user's answer.
Then run: pexo-chat.sh <project_id> "{user's exact answer}"
Go back to Step 5.
Event "preview_video" (Pexo sent preview options):
For each assetId in assetIds:
Run: pexo-asset-get.sh <project_id> <assetId>
Copy the "url" field from the returned JSON.
Show all preview URLs to the user with labels (A, B, C...).
Ask the user to pick one.
After user picks:
Run: pexo-chat.sh <project_id> "{user's choice}" --choice <selected_asset_id>
Go back to Step 5.
Event "document":
Mention the document to the user.
"DELIVER" →
Go to Step 7.
"FAILED" →
Go to Step 8.
"RECONNECT" →
Run: pexo-chat.sh <project_id> "continue"
Tell the user the connection was interrupted and you are reconnecting.
Go back to Step 5.
Step 7. Deliver the final video.
7a. Find the final_video event in recentMessages. Get the assetId.
7b. Run: pexo-asset-get.sh <project_id> <assetId>
7c. Show the downloaded video file to the user.
7d. Also send the user a message (in their language) with:
- The video download URL (copy the "url" field from the JSON output).
Send the FULL URL as plain text, including all query parameters.
Example:
https://pexo-assets.oss-us-east-1.aliyuncs.com/projects%2F123%2Fassets%2Fvideo.mp4?OSSAccessKeyId=xxx&Expires=xxx&Signature=xxx
- Project page: https://pexo.ai/project/{project_id}
- Ask if satisfied or want revisions.
Common delivery mistakes to avoid:
✗ Truncated URL (missing ?OSSAccessKeyId=...&Signature=...) → 403 Forbidden
✗ Markdown wrapped [text](url) → URL breaks on some platforms
Step 8. Handle failure.
8a. Read the nextActionHint field from the JSON.
8b. Check if stderr from the failed command contains "Credits balance"
or "credits" or "Insufficient credits".
If yes → Go to Credit Error Handling below.
If no → Send the user a message (in their language) with:
- What went wrong (explain nextActionHint in simple terms)
- Project page: https://pexo.ai/project/{project_id}
- Offer to retry.
Step 9. Timeout.
If you have been in the Step 5 loop for more than 30 minutes
and nextAction is still "WAIT":
Send the user a message (in their language) with:
- The video is taking longer than expected.
- Project page: https://pexo.ai/project/{project_id}
- Help guide: https://pexo.ai/connect/openclaw
- Ask whether to keep waiting or start over.
Stop polling. Wait for user instructions.
When any command fails and stderr contains credit-related information (look for: "Credits balance", "credits", or "Insufficient credits"):
Step A. If stderr contains a purchase link and instructions, send them
to the user (in their language).
Step B. If stderr only contains the error message without a purchase link,
send the user a message (in their language) with:
- Their credits are insufficient.
- To add credits: visit https://pexo.ai/home
→ click Credits (top-right) → Buy Credits → Extra Credits.
Step C. After the user confirms they have added credits, retry the failed step.
Step 1. Use the same project_id.
Step 2. Run: pexo-chat.sh <project_id> "{user's exact feedback}"
Step 3. Go to Step 5 of the main workflow (start polling).
Pexo cannot crawl web URLs. If the user provides a link to a file, download it first, then upload.
Upload and reference workflow:
# Upload the file
asset_id=$(pexo-upload.sh <project_id> photo.jpg)
# Reference the asset in your message to Pexo
pexo-chat.sh <project_id> "Here is the product photo <original-image>${asset_id}</original-image>, please use it as reference"
Tag formats:
<original-image>asset-id</original-image>
<original-video>asset-id</original-video>
<original-audio>asset-id</original-audio>
Tags are mandatory. Bare asset IDs in pexo-chat.sh messages are ignored by Pexo.
| Script | Usage | Returns |
|---|---|---|
pexo-project-create.sh |
[project_name] or --name <n> |
project_id string. On 429, credit info printed to stderr. |
pexo-project-list.sh |
[page_size] or --page <n> --page-size <n> |
Projects JSON |
pexo-project-get.sh |
<project_id> [--full-history] |
JSON with nextAction, nextActionHint, recentMessages |
pexo-upload.sh |
<project_id> <file_path> |
asset_id string |
pexo-chat.sh |
<project_id> <message> [--choice <id>] [--timeout <s>] |
Acknowledgement JSON (async). On 429/412 or credit errors, error info printed to stderr. |
pexo-asset-get.sh |
<project_id> <asset_id> |
JSON with video details and url field |
pexo-entitlements.sh |
(no args) | JSON with credits and plan info. Called automatically by other scripts on credit errors. |
pexo-doctor.sh |
(no args) | Diagnostic report |
Load these when needed:
references/SETUP-CHECKLIST.mdreferences/TROUBLESHOOTING.mdMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
Useful defaults in pexo-agent — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: pexo-agent is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added pexo-agent from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for pexo-agent matched our evaluation — installs cleanly and behaves as described in the markdown.
pexo-agent reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: pexo-agent is focused, and the summary matches what you get after install.
Useful defaults in pexo-agent — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
pexo-agent is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: pexo-agent is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend pexo-agent for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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