tiktok-android_skill

This skill automates TikTok engagement on Android via ADB, guiding setup and enabling topic-based posting with static or AI-generated comments.

Python

2.5k

GitHub Stars

9

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill openclaw/skills --skill tiktok-android

_meta.json281 B
config.example.py2.5 KB
README.md11.7 KB
requirements.txt47 B
run_complete_session.py7.1 KB
run_full_campaign.py11.5 KB
setup.py9.7 KB
SKILL.md7.8 KB
tiktok_bot.py12.8 KB

Overview

This skill automates TikTok engagement on Android devices using ADB to search topics, browse the For You feed, and post contextual comments. It includes an interactive setup wizard, two comment modes (static templates or AI-generated), duplicate prevention, and flexible configuration saved locally. Use it to run controlled engagement campaigns while avoiding repeated comments.

How this skill works

The bot drives a logged-in TikTok app over ADB: it searches topics or scrolls the For You feed, captures video screenshots when needed, generates comments (from templates or via an AI provider), and posts them. It tracks which videos have been commented on to prevent duplicates, and includes coordinate customization for different screen resolutions. A setup wizard creates config files and optional .env API credentials.

When to use it

Run targeted campaigns to engage audiences around specific topics or niches.
Grow social presence by leaving high-quality, contextual comments on relevant videos.
Test comment strategies safely on an Android test account before scaling to main accounts.
Automate intermittent engagement sessions (daily/weekly) while monitoring account health.
Use AI-generated comments when context-sensitive replies are needed; use static mode for low-cost, high-throughput runs.

Best practices

Start with a fresh or aged account and perform manual browsing before automation to blend behavior.
Limit volume: begin with 3–5 videos, then scale up but keep ~25–30 comments/day per account max.
Prefer 10–25 word, specific comments that reference visible elements; avoid self-promotion and repetitive phrases.
Customize tap coordinates for your device resolution and verify with screenshots before full runs.
Rotate topics, comment styles, and posting times; include breaks to reduce detection risk.

Example use cases

Daily fitness engagement: search "fitness" and post 5 context-aware comments using static templates.
Explore-mode warmup: comment on 10 random For You videos to build account activity before a campaign.
Niche outreach: run targeted searches across multiple topics (e.g., cooking, travel) with different comment sets per topic.
AI-driven engagement: use Claude/OpenAI to generate contextual questions that prompt replies and profile visits.
Scheduled campaigns: integrate with cron to run short sessions at varied times for sustained presence.

FAQ

No—static template mode requires no API key. AI mode requires API credentials (Anthropic/OpenAI/OpenRouter) stored in a .env file.

How do I handle different screen sizes?

Take a device screenshot via ADB, identify target coordinates, and update the navigation coordinates file. The skill includes guidance and a COORDINATES reference.