Skill: agenticio/tiktok (version 3.0.0)

--- name: tiktok description: 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. --- # 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.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)