TikTok

Local-first TikTok Growth OS for strategy, hooks, scripts, retention design, and analytics feedback. Use when the user mentions TikTok, short-form video, hoo...

Security Scan

This is an internally consistent, local-first TikTok content authoring and analytics helper: it stores JSON files under your home directory and contains only CLI scripts and guidance with no network access or credential requests.

Purpose & Capability

The name/description (TikTok Growth OS) matches the included scripts and documentation: scripts implement profile management, saving/browsing content, logging performance, and summarizing patterns. Nothing in the manifest or code asks for unrelated capabilities (cloud credentials, platform APIs, posting automation).

Instruction Scope

SKILL.md scopes behavior to local content generation, optional local saving, and using locally logged analytics. Instructions do not direct reading of unrelated system files, network calls, scraping, or posting; they explicitly state 'No API, no posting, no platform automation.'

Install Mechanism

No install spec is present (instruction-only). The package includes only small Python scripts and reference docs; there are no downloads, external installers, or archive extraction steps.

Credentials

The skill declares no required environment variables, binaries, or credentials. The only persistent state is written to ~/.openclaw/workspace/memory/tiktok — consistent with the stated local-memory behavior.

Persistence & Privilege

always is false and the skill does not request system-wide changes. It writes only to its own subdirectory under the user's home and does not modify other skills or system configs.

Assessment

This skill appears to do what it says: generate and save TikTok ideas, hooks, scripts, and simple analytics locally. Before installing, consider: (1) It will create and update files at ~/.openclaw/workspace/memory/tiktok (profile, content_bank, analytics, pattern_report) — data is stored unencrypted as JSON. (2) Review the included scripts if you are concerned about privacy or exfiltration; these scripts perform only local file I/O and display output. (3) Avoid logging sensitive or personally identifiable data into the analytics or content files. (4) Run the Python scripts in a controlled environment (virtualenv) if you plan to execute them. (5) Because the agent can invoke skills autonomously by default, only enable/use this skill if you are comfortable with the agent creating or updating those local files. If you'd like, I can point out exact lines where files are read/written or help you modify the storage path or add encryption.

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.