tiktok

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.

3,891 stars

Best use case

tiktok is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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.

Teams using tiktok should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/tiktok/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/agenticio/tiktok/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/tiktok/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How tiktok Compares

Feature / AgenttiktokStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# TikTok Growth OS

A local-first operating system for TikTok creators.
Focus on retention, repeatability, and strategic content design rather than random virality.

## What this skill does

Use this skill when the user wants help with:
- TikTok niche positioning
- content pillars
- video ideas
- hooks
- short-form scripts
- A/V storyboard formatting
- series planning
- captions and hashtags
- retention diagnosis
- performance pattern review

This skill should produce execution-ready outputs, not vague inspiration.

## Core operating logic

TikTok growth is treated as a system of controllable variables:

- **Hook strength**: Does the first 1–3 seconds create tension or relevance?
- **Retention design**: Does the script create momentum and payoff?
- **Visual pacing**: Is there a pattern interrupt every few seconds?
- **Audience fit**: Does this feel native to the target viewer?
- **Series potential**: Can this idea create repeated return behavior?
- **Data feedback**: What should be repeated, refined, or dropped?

Do not present growth as magic.
Do not guarantee virality or follower gains.
Always frame outputs as strategic guidance.

## Output rules

When generating TikTok content, prefer:
- spoken-language phrasing
- short sentences
- immediate tension
- specific audience fit
- clear payoff
- native short-form rhythm

Avoid:
- essay-style intros
- generic motivational filler
- slow setup with no payoff
- over-explaining before the hook lands

## Default content workflow

When the user asks for TikTok help, structure work in this order when relevant:

1. clarify niche or audience if already known from local memory
2. generate 3–10 content angles
3. produce 5 hook variations
4. build one execution-ready script
5. optionally save the result to local memory
6. if analytics exist, use prior performance to refine the output

## Hook generation rules

Hooks should usually fall into one of these buckets:
- curiosity gap
- painful truth
- contrarian take
- mistake warning
- identity-based recognition
- specific promise
- emotional confession
- authority / signal of experience

When generating hooks:
- make each variation meaningfully different
- label the type
- explain briefly why it may work
- avoid repeating the same sentence shape

## Script generation rules

When writing TikTok scripts, default to this format:

| Time | Visual | Spoken / Audio | On-Screen Text |
|------|--------|----------------|----------------|

Guidelines:
- first 1–3 seconds must carry the hook
- each segment should add tension, clarity, or payoff
- include pattern interrupts where useful
- optimize for vertical, short-form pacing
- include CTA only if it fits naturally

## Performance review rules

If the user provides metrics or performance context, diagnose using first principles such as:
- weak opening
- slow payoff
- too much setup
- vague topic framing
- mismatch between title/hook and delivery
- insufficient visual momentum
- weak emotional or practical value
- unclear audience targeting

## Local memory

All files are stored locally only in:

`~/.openclaw/workspace/memory/tiktok/`

Files:
- `profile.json` — niche, audience, goals, pillars
- `content_bank.json` — saved ideas, hooks, scripts, captions, notes
- `analytics.json` — manually logged video performance
- `pattern_report.json` — latest summarized learning report

## Scripts

| 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

- `references/hooks.md`
- `references/retention.md`

## Safety boundaries

- Local-only storage
- No TikTok API
- No account login
- No posting
- No scraping
- No engagement automation
- No claims of guaranteed virality

The user is responsible for final review, posting, and platform compliance.

Related Skills

TikTok B2B 引流台词生成器

3891
from openclaw/skills

## 技能描述

Content & Documentation

tiktok-app-marketing

3891
from openclaw/skills

Automate TikTok slideshow marketing for any app or product. Researches competitors, generates AI images, adds text overlays, posts via Postiz, tracks analytics, and iterates on what works. Use when setting up TikTok marketing automation, creating slideshow posts, analyzing post performance, optimizing app marketing funnels, or when a user mentions TikTok growth, slideshow ads, or social media marketing for their app. Covers competitor research (browser-based), image generation, text overlays, TikTok posting (Postiz API), cross-posting to Instagram/YouTube/Threads, analytics tracking, hook testing, CTA optimization, conversion tracking with RevenueCat, and a full feedback loop that adjusts hooks and CTAs based on views vs conversions.

tiktok-slideshow

3891
from openclaw/skills

Creates TikTok image carousels (slideshows with text overlays on photos) via the ViralBaby API. Use when the user wants to: create TikTok slideshows or carousels, find/search for background images for social media content, post or upload slideshow content to TikTok, edit slide text, or manage image collections for content creation. Do NOT use for: general TikTok account management, TikTok analytics or metrics, video editing or video creation (this is for photo slideshows only), non-TikTok social media platforms, or any task unrelated to creating visual slideshow content for TikTok.

TikTok Profile Scraper

3891
from openclaw/skills

A browser-based TikTok profile discovery and scraping tool.

tiktok-trend-slayer

3891
from openclaw/skills

TikTok 选品猎手 - 自动监控 TikTok 商品榜与达人榜,利用 AI 挖掘高增长爆款,生成选品及达人撮合策略。当用户需要 TikTok 选品分析、爆款挖掘、达人匹配、趋势监控时使用此技能。

---

3891
from openclaw/skills

name: article-factory-wechat

Content & Documentation

humanizer

3891
from openclaw/skills

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Content & Documentation

find-skills

3891
from openclaw/skills

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

General Utilities

tavily-search

3891
from openclaw/skills

Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.

Data & Research

baidu-search

3891
from openclaw/skills

Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.

Data & Research

agent-autonomy-kit

3891
from openclaw/skills

Stop waiting for prompts. Keep working.

Workflow & Productivity

Meeting Prep

3891
from openclaw/skills

Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.

Workflow & Productivity