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.

Safety Notice

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Install skill "tiktok" with this command: npx skills add agenticio/tiktok

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:

TimeVisualSpoken / AudioOn-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

ScriptPurpose
scripts/manage_account.pyCreate or update account profile
scripts/save_content.pySave ideas, hooks, scripts, captions, or notes
scripts/list_content.pyBrowse local content assets
scripts/log_performance.pyLog manual TikTok performance data
scripts/analyze_patterns.pySummarize 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.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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