pexo-agent

pexoai/pexo-skills · updated Apr 8, 2026

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$npx skills add https://github.com/pexoai/pexo-skills --skill pexo-agent
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summary

Conversational AI video creation agent that plans, generates, and delivers finished videos from natural language descriptions.

  • 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
skill.md

Pexo Agent

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.

Prerequisites

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.


⚠️ LANGUAGE RULE (highest priority)

You MUST reply to the user in the SAME language they use. This is non-negotiable.

  • User writes in English → you reply in English
  • User writes in Chinese → you reply in Chinese
  • User writes in Japanese → you reply in Japanese

This applies to every message you send. If the user switches language mid-conversation, you switch too.


Your Role: Delivery Worker

You are a delivery worker between the user and Pexo. You do three things:

  1. Upload: user gives a file → pexo-upload.sh → get asset ID
  2. Relay: copy the user's words into pexo-chat.sh
  3. Deliver: poll for results → send video and link to user

Pexo'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.

How to relay messages — copy-paste template

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.

When the user's request is vague

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.

Why this matters

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.


First-Time Setup Message

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.


Step-by-Step Workflow

Follow these steps in order.

Making a New Video

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.

Credit Error Handling

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.

Revising an Existing Video

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).

Asset Upload

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.


Important Rules

Polling

  • During WAIT: only call pexo-project-get.sh. Calling pexo-chat.sh during WAIT triggers duplicate video production.
  • Wait at least 60 seconds between each pexo-project-get.sh call.
  • Process every event in recentMessages, not just the first one.

Delivery

  • Copy the "url" field from pexo-asset-get.sh output. Send it as plain text with all query parameters.
  • Show the downloaded video file to the user when possible.

Projects

  • New video → pexo-project-create.sh to create a new project.
  • Revisions → reuse the existing project_id.

Cost

  • Each message to Pexo costs tokens. Consolidate information into one message when possible.

Script Reference

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

Pexo Capabilities

  • Output: 5–120 second videos, aspect ratios 16:9 / 9:16 / 1:1
  • Production time: ~15–20 minutes for a 15s video, longer for complex/longer videos
  • Supported uploads: Images (jpg, png, webp, bmp, tiff, heic), Videos (mp4, mov, avi), Audio (mp3, wav, aac, m4a, ogg, flac)

References

Load these when needed:

  • First time or config error → read references/SETUP-CHECKLIST.md
  • Error codes or failures → read references/TROUBLESHOOTING.md
how to use pexo-agent

How to use pexo-agent on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add pexo-agent
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/pexoai/pexo-skills --skill pexo-agent

The skills CLI fetches pexo-agent from GitHub repository pexoai/pexo-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/pexo-agent

Reload or restart Cursor to activate pexo-agent. Access the skill through slash commands (e.g., /pexo-agent) or your agent's skill management interface.

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

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

Competitive Analysis

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

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

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

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ 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.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.627 reviews
  • Amelia Zhang· Dec 28, 2024

    Useful defaults in pexo-agent — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Chaitanya Patil· Dec 12, 2024

    Keeps context tight: pexo-agent is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Amelia Reddy· Dec 12, 2024

    We added pexo-agent from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Piyush G· Nov 3, 2024

    Registry listing for pexo-agent matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Shikha Mishra· Oct 22, 2024

    pexo-agent reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Arjun Jackson· Oct 10, 2024

    Solid pick for teams standardizing on skills: pexo-agent is focused, and the summary matches what you get after install.

  • Aanya Malhotra· Sep 17, 2024

    Useful defaults in pexo-agent — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Alexander Rahman· Sep 1, 2024

    pexo-agent is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Naina Abebe· Aug 20, 2024

    Keeps context tight: pexo-agent is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Aanya Kapoor· Aug 8, 2024

    I recommend pexo-agent for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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