pexoai-agent

Overview of pexoai-agent skill

Pexoai-agent is a shell-script-backed skill for sending short-form video jobs to Pexo’s hosted video agent. It is best for users who want an AI system to handle the creative production loop—script, shots, transitions, music, and preview selection—without building a custom video pipeline themselves. The real job-to-be-done is not “generate text about a video,” but “create and manage an actual short video project from prompt to asset retrieval.”

What pexoai-agent actually does

The pexoai-agent skill is designed for videos roughly 5 to 120 seconds long. It supports common short-video formats such as product promos, explainers, social clips, brand videos, and creator-style content, with aspect ratios including 16:9, 9:16, and 1:1.

Unlike a generic prompt, this skill gives the agent a concrete operating path:

• create a project
• submit a message to Pexo
• optionally upload assets
• poll project status
• fetch generated assets

Best fit users

This pexoai-agent skill is a strong fit if you:

• want AI-assisted video generation, not just ideation
• are comfortable with API-key setup and shell tooling
• need a repeatable workflow for short-form video production
• want an agent to relay user requests into a production backend

It is especially relevant for pexoai-agent for Video Editing style use cases where the user wants a finished short video or revisions, not timeline-level manual editing controls.

Main differentiators vs ordinary prompting

The most important advantage is operational structure. The repo includes purpose-built scripts such as:

• scripts/pexo-project-create.sh
• scripts/pexo-chat.sh
• scripts/pexo-project-get.sh
• scripts/pexo-upload.sh
• scripts/pexo-asset-get.sh
• scripts/pexo-doctor.sh

That means the pexoai-agent guide is more than prompt wording: it gives you an installable workflow with diagnostics, backend interaction, and clearer error handling.

Important constraints before you install

This is not a local video generation tool. You need:

• a Pexo account and API key
• PEXO_API_KEY
• PEXO_BASE_URL
• local CLI dependencies: curl, jq, file

It also assumes an agent environment that can run shell scripts. If your setup cannot execute local scripts or store config under ~/.pexo/config, adoption will be harder.

Biggest adoption blockers to know early

The main blockers are practical, not conceptual:

• missing config in ~/.pexo/config
• invalid or expired API key
• shell dependency gaps
• misunderstanding that pexo-chat.sh submits work asynchronously rather than streaming final output
• incorrect asset references in prompts

Those are manageable, but they matter more than repo polish when deciding whether the pexoai-agent install is worth your time.

How to Use pexoai-agent skill

Install context for pexoai-agent

If you use a skills-based agent runtime, add the skill from the pexoai/pexo-skills repository and then work from the files in skills/pexo-agent. After installation, treat this as a shell-assisted API workflow rather than a pure prompt pack.

Because the skill itself does not center on a one-command bootstrap script, your real setup starts with config and diagnostics.

Set up required config first

Create the config file exactly where the scripts expect it:

mkdir -p ~/.pexo
cat > ~/.pexo/config << 'EOF'
PEXO_BASE_URL="https://pexo.ai"
PEXO_API_KEY="sk-<your-api-key>"
EOF

This is the single most important step in any pexoai-agent install. The shared script layer auto-loads this file, and environment variables can override it if needed.

Run diagnostics before your first request

Use the doctor script before trying to create a project:

pexo-doctor.sh

This checks:

• config file presence
• required variables
• curl, jq, and file
• network reachability
• whether your API key can actually access Pexo

If diagnostics fail, fix those issues first. That is faster than debugging later errors in project creation or chat submission.

Verify the environment with a safe read call

After diagnostics, confirm the environment with:

pexo-project-list.sh

If it returns JSON, your pexoai-agent usage path is likely ready. This is a better first verification than immediately attempting a full creative request.

Understand the actual workflow

The practical workflow is:

1. Create a project
2. Optionally upload source assets
3. Send a production request message
4. Poll project state
5. Retrieve final assets

Typical command flow:

project_id="$(pexo-project-create.sh "New Product Teaser")"
pexo-chat.sh "$project_id" "Create a 20-second 9:16 product teaser for a skincare serum."
pexo-project-get.sh "$project_id"

If your workflow includes user-provided media, upload first and then reference the resulting asset IDs correctly in the message.

How asset references work in prompts

One of the highest-value details in this pexoai-agent guide is that bare asset IDs are not enough. The chat script expects tagged references such as:

• <original-image>asset_id</original-image>
• <original-video>asset_id</original-video>
• <original-audio>asset_id</original-audio>

That matters because pexo-chat.sh validates this locally and will reject malformed usage before the backend can help you.

A stronger message looks like:

Create a 15-second vertical ad for this product image <original-image>a_ABC123</original-image>.
Tone: premium but friendly.
Audience: women 25–40.
Include a short hook in the first 2 seconds.
End with a CTA: "Shop now".

What inputs produce better video results

The pexoai-agent skill works better when your request is production-shaped, not vague. Include:

• goal
• duration
• aspect ratio
• audience
• platform
• tone
• key message
• must-include visuals or assets
• CTA
• hard constraints

Weak prompt:

Make a video for my product.

Stronger prompt:

Create a 30-second 9:16 TikTok-style product video for a portable blender.
Audience: busy students and office workers.
Goal: drive clicks to product page.
Tone: energetic, clean, modern.
Must show portability, USB charging, and smoothie use cases.
Include on-screen text in short phrases.
End with: "Blend anywhere."

The stronger version reduces guesswork around pacing, framing, and conversion intent.

Suggested pexoai-agent usage pattern for revisions

Treat the first submission as a draft request, then iterate with specific deltas:

• shorten intro
• make opening hook stronger
• swap music mood
• emphasize one product benefit
• pick a preview option if offered

The repo signals that Pexo may ask clarifying questions or offer previews. That means your best workflow is not “one prompt and done,” but “submit, inspect, choose, refine.”

Files to read first in the repository

For fast understanding, read these in order:

1. SKILL.md
2. references/SETUP-CHECKLIST.md
3. references/TROUBLESHOOTING.md
4. scripts/pexo-doctor.sh
5. scripts/pexo-chat.sh
6. scripts/pexo-project-create.sh
7. scripts/pexo-project-get.sh
8. scripts/pexo-asset-get.sh

This path gives you setup, failure modes, and the exact request lifecycle before you inspect lower-level implementation details.

What to expect from async submission

A common misunderstanding in pexoai-agent usage is assuming pexo-chat.sh returns the finished video. It does not. It submits the request and confirms the SSE stream opened, then disconnects intentionally.

So your agent should treat this as an async job system:

• pexo-chat.sh submits
• pexo-project-get.sh checks progress
• pexo-asset-get.sh retrieves downloadable asset details

That distinction changes how you design automations and user expectations.

Common errors that matter in real use

From the repo’s troubleshooting notes, the most decision-relevant errors are:

• 401: invalid API key or auth failure
• 404: missing project or asset
• 412: incompatible project agent version
• 429: rate limit, daily creation limit, or project video limit
• 403: expired signed asset download URL

The scripts also use meaningful exit behavior:

• 0: success
• 1: request or backend failure
• 2: local usage error

That is useful if you want to wrap pexoai-agent in a larger automation.

pexoai-agent skill FAQ

Is pexoai-agent beginner-friendly?

Moderately. The pexoai-agent skill is easier than building your own video backend, but not as simple as a chat-only skill. You need to be comfortable with config files, shell scripts, and async workflow concepts.

If you are a complete beginner to CLI tooling, expect some setup friction.

When should I use pexoai-agent instead of a normal LLM prompt?

Use pexoai-agent when you want the agent to operate a real video-generation service with project state, uploads, and downloadable assets. Use a normal prompt when you only need creative planning, storyboarding, or script suggestions without backend execution.

Is pexoai-agent for Video Editing or full video generation?

It leans more toward AI video generation and production orchestration than timeline-based manual editing. If your need is “turn this brief into a short video,” it fits well. If your need is frame-accurate editing decisions inside a traditional NLE workflow, this is not the same thing.

Does pexoai-agent support user assets?

Yes. The workflow includes upload and asset retrieval scripts, and the chat path supports referenced media. But the references must be wrapped in the expected XML-like tags, not pasted as raw IDs.

What are the main limits of the skill?

The biggest limits are:

• short-video scope
• dependence on Pexo’s backend and account access
• async processing rather than immediate final output
• possible quota or rate-limit constraints
• less suitability for highly manual editing control

Can I use pexoai-agent in a multilingual workflow?

Yes, and the skill explicitly prioritizes replying in the same language as the user. That is operationally important if your agent serves multilingual users, because language consistency is a hard instruction in the skill.

What should I do if pexoai-agent fails right after install?

Run:

pexo-doctor.sh

Then inspect:

• references/SETUP-CHECKLIST.md
• references/TROUBLESHOOTING.md

Most early failures come from config, dependencies, connectivity, or API auth—not from the creative request itself.

How to Improve pexoai-agent skill

Give pexoai-agent production-ready briefs

The fastest way to improve results is to stop giving generic asks. Better briefs include:

• exact duration
• target platform
• aspect ratio
• audience
• message hierarchy
• visual inputs
• style references in plain language
• CTA
• restrictions

This improves both creative quality and reduces clarification loops.

Make constraints explicit, not implied

If something matters, say it directly:

• “No voiceover”
• “Use upbeat background music”
• “Keep text minimal”
• “No medical claims”
• “Prioritize first 3 seconds for hook”
• “Use 9:16 vertical framing”

Pexoai-agent can only operationalize constraints it receives clearly.

Use revision prompts as change requests

After the first output, do not ask for “better.” Ask for a controlled change:

• “Keep the same concept, but cut total runtime to 12 seconds”
• “Use a more premium tone and slower transitions”
• “Replace broad lifestyle shots with closer product detail emphasis”

This makes the second pass much more usable than broad dissatisfaction.

Handle uploads and asset references carefully

A common failure mode is weak input hygiene:

• uploading the wrong file
• referencing the wrong asset ID
• forgetting the <original-image> style wrapper
• assuming a signed asset URL stays valid forever

If your workflow depends on external media, be strict about file tracking and message formatting.

Build around async polling, not instant completion

To improve pexoai-agent usage in agents or automations, design for delayed completion:

• submit the request
• store the project ID
• poll with backoff
• fetch assets only when ready
• surface meaningful status to the user

Many user frustrations come from treating the system like synchronous chat instead of a job queue.

Use the troubleshooting docs before editing scripts

If output fails or behavior is inconsistent, read:

• references/TROUBLESHOOTING.md
• scripts/_common.sh

The shared layer already standardizes auth, request handling, and compact error output. In many cases, you do not need to modify scripts—you need to interpret the existing error shape correctly.

Improve reliability with preflight checks

If you plan to use pexoai-agent repeatedly, create a preflight habit:

• run pexo-doctor.sh
• verify project listing
• confirm asset availability
• check for quotas or expired auth before user-facing submission

This prevents avoidable failures during real production use.

Know when not to use pexoai-agent

Do not use pexoai-agent when:

• you need offline/local-only generation
• you cannot store API credentials safely
• your environment cannot run shell scripts
• you need deep manual editing controls instead of AI-produced outputs
• your job is only creative brainstorming, not execution

That clarity improves installation decisions more than another feature list would.