tweet-promote

name	tweet-promote
description	AUTONO reasons about how to promote its token, then calls Venice video generation to produce promotional videos and queues them for broadcast.
var
tags	["twitter","content","video","venice","promotion"]

Generate promotional content for AUTONO's token. This combines strategic reasoning with Venice video generation — the output is a video queued for posting.

Step 1: Load context

Read before generating anything:

1. memory/goals.json — current mode, DIEM balance, earnings rate, milestones
2. memory/x-performance.jsonl — which content types get the most engagement; what has performed well in the last 30 days
3. memory/x-tweet-log.jsonl — recent tweets; avoid repeating a topic from the last 7 days
4. memory/lp-positions.jsonl — current LP state; use real numbers
5. identity/SOUL.md — voice, values, what AUTONO cares about

Step 2: Reason about promotion strategy

Think through what would make a compelling promotional video RIGHT NOW. Consider:

• What is the most interesting/shareable fact about AUTONO today? (DIEM earned, days to build mode, LP size, on-chain activity)
• What narrative thread is strongest? (accumulate → build arc, self-funding agent, Venice inference gating)
• What would make a crypto-native viewer stop and watch?
• What content type has performed best recently (from x-performance.jsonl)?

Write your reasoning to memory/x-promote-strategy.md (overwrite each run):

# Promote strategy — {date}

## What's notable right now
{2-3 sentences on current state}

## Chosen angle
{The specific story this video tells}

## Prompt plan
{What to show, what narration, what data points}

Step 3: Generate video via Venice API

Call the Venice video generation API using the VENICE_API_KEY secret. Venice supports image-to-video and text-to-video. Choose the appropriate endpoint based on what you want to create.

Text-to-video request

curl -s -X POST "https://api.venice.ai/api/v1/image/generate" \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan-2.1-t2v-480p",
    "prompt": "<your prompt here>",
    "width": 854,
    "height": 480,
    "steps": 30
  }'

Available Venice video models

Model	Type	Best for
wan-2.1-t2v-480p	text-to-video, 480p	Short clips, on-chain data visualizations
wan-2.1-t2v-720p	text-to-video, 720p	Higher quality promotional content
wan-2.1-i2v-480p	image-to-video	Animating a static chart or logo
wan-2.1-i2v-720p	image-to-video, 720p	Premium animated content

Default to wan-2.1-t2v-480p for speed. Use 720p when quality matters more than cost.

Prompt guidelines

• Lead with the visual: describe exactly what the viewer sees in the first frame
• Include the specific on-chain facts as on-screen text elements
• Keep narration implicit — the video tells the story visually
• 5-10 seconds is ideal for Twitter video

Example prompt structure:

Dark terminal screen. Green monospace text scrolls: "DIEM earned today: 0.485". 
Camera slowly pulls back to reveal a network of glowing nodes on Base chain. 
The words "self-funding autonomous agent" appear in white at bottom. 
Cinematic, minimal, crypto-native aesthetic.

Step 4: Handle the response

Venice returns the video as a URL or base64. Save it:

# If URL response: download it
curl -s "{video_url}" -o "memory/videos/promo-{date}-{slug}.mp4"

# If base64: decode it
echo "{base64_data}" | base64 -d > "memory/videos/promo-{date}-{slug}.mp4"

Create memory/videos/ if it doesn't exist.

Step 5: Queue for broadcast

Write a tweet file that references the video. Twitter requires the video be attached at post time — the tweet text accompanies it:

Write .pending-x/tweet-{YYYYMMDD-HHMMSS}-promote.txt:

#content_type:promote
#video:memory/videos/promo-{date}-{slug}.mp4
{tweet text — max 240 chars, no URL unless attaching video via API}

Note: The #video: line is metadata for the operator to handle video upload — the current tweet-browser.py posts text only. Video uploads require the X Media Upload API (separate step). Flag this in the file so the operator knows manual upload is needed if video upload isn't automated yet.

Step 6: Log

Write to memory/logs/{today}.md:

tweet-promote: strategy angle: {angle} | model: {model} | video saved: {filename} | queued: tweet-{timestamp}-promote.txt

Fallback: image-only if video generation fails

If Venice video API returns an error, fall back to a compelling static image generated via Venice image API:

curl -s -X POST "https://api.venice.ai/api/v1/image/generate" \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "flux-dev-uncensored",
    "prompt": "<your prompt here>",
    "width": 1200,
    "height": 675,
    "steps": 30
  }'

Save as memory/videos/promo-{date}-{slug}.png and mark the pending file with #image: instead of #video:.

Log the fallback: tweet-promote: video failed ({error}), fell back to image.