Local-first TikTok Growth OS for strategy, hooks, scripts, retention design, and analytics feedback. Use when the user mentions TikTok, short-form video, hooks, scripts, retention, virality, content pillars, series planning, account positioning, or performance review. Generates execution-ready outputs and stores all assets locally. No API, no posting, no platform automation.
A local-first operating system for TikTok creators. Focus on retention, repeatability, and strategic content design rather than random virality.
Use this skill when the user wants help with:
This skill should produce execution-ready outputs, not vague inspiration.
TikTok growth is treated as a system of controllable variables:
Do not present growth as magic. Do not guarantee virality or follower gains. Always frame outputs as strategic guidance.
When generating TikTok content, prefer:
Avoid:
When the user asks for TikTok help, structure work in this order when relevant:
Hooks should usually fall into one of these buckets:
When generating hooks:
When writing TikTok scripts, default to this format:
| Time | Visual | Spoken / Audio | On-Screen Text |
|---|
Guidelines:
If the user provides metrics or performance context, diagnose using first principles such as:
All files are stored locally only in:
~/.openclaw/workspace/memory/tiktok/
Files:
profile.json — niche, audience, goals, pillarscontent_bank.json — saved ideas, hooks, scripts, captions, notesanalytics.json — manually logged video performancepattern_report.json — latest summarized learning report| Script | Purpose |
|---|---|
scripts/manage_account.py | Create or update account profile |
scripts/save_content.py | Save ideas, hooks, scripts, captions, or notes |
scripts/list_content.py | Browse local content assets |
scripts/log_performance.py | Log manual TikTok performance data |
scripts/analyze_patterns.py | Summarize local performance patterns |
references/hooks.mdreferences/retention.mdThe user is responsible for final review, posting, and platform compliance.