Tiktok Account Audit
aronhy/tiktok-agent-skills
A skill your agent uses when a user provides a TikTok profile or account link and asks for account analysis, competitor research, content or commerce performance, operational-logic research…
A skill your agent uses to reverse-engineer why a piece of content went viral (or overperformed) — yours or someone else's — and extract the repeatable mechanism to apply to your own content.
Install Viral Reverse Engineering
$ npx skills add social-media-skills/skills --skill viral-reverse-engineering -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install social-media-skills/skills viral-reverse-engineering --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/viral-reverse-engineering .claude/skills/viral-reverse-engineering && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "viral-reverse-engineering" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/viral-reverse-engineering into .claude/skills/viral-reverse-engineering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "viral-reverse-engineering", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/social-media-skills/skills/tree/main/skills/viral-reverse-engineeringType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add social-media-skills/skills --skill viral-reverse-engineering -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install social-media-skills/skills viral-reverse-engineering --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/viral-reverse-engineering .agents/skills/viral-reverse-engineering && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "viral-reverse-engineering" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/viral-reverse-engineering into .agents/skills/viral-reverse-engineering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "viral-reverse-engineering", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add social-media-skills/skills --skill viral-reverse-engineering -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install social-media-skills/skills viral-reverse-engineering --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/viral-reverse-engineering .cursor/skills/viral-reverse-engineering && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "viral-reverse-engineering" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/viral-reverse-engineering into .cursor/skills/viral-reverse-engineering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "viral-reverse-engineering", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/social-media-skills/skills.git --path skills/viral-reverse-engineering--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add social-media-skills/skills --skill viral-reverse-engineering -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install social-media-skills/skills viral-reverse-engineering --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/viral-reverse-engineering .gemini/skills/viral-reverse-engineering && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "viral-reverse-engineering" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/viral-reverse-engineering into .gemini/skills/viral-reverse-engineering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "viral-reverse-engineering", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install social-media-skills/skills viral-reverse-engineeringInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add social-media-skills/skills --skill viral-reverse-engineering -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/viral-reverse-engineering .github/skills/viral-reverse-engineering && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "viral-reverse-engineering" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/viral-reverse-engineering into .github/skills/viral-reverse-engineering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "viral-reverse-engineering", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add social-media-skills/skills --skill viral-reverse-engineering -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install social-media-skills/skills viral-reverse-engineering --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/viral-reverse-engineering .opencode/skills/viral-reverse-engineering && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "viral-reverse-engineering" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/viral-reverse-engineering into .opencode/skills/viral-reverse-engineering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "viral-reverse-engineering", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
viral-reverse-engineering- GitHub stars
- 134
- Token cost
- ~1.9k tokens
- SKILL.md length
- 797 words
- Files
- 7 (incl. references)
- Skills in repo
- 106
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses to reverse-engineer why a piece of content went viral (or overperformed) — yours or someone else's — and extract the repeatable mechanism to apply to your own content.
- Works in 7 steps: Read the foundation → Source the content (the step everyone… → Deconstruct (the teardown) → …
- Reverse-engineer why a piece of content went viral (or overperformed) — yours
- SKILL.md covers Step 0 — Read the foundation, Step 1 — Source the content…, Step 2 — Deconstruct (the… and Step 3 — Isolate the real…, plus 7 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Viral Reverse Engineering is an agent skill from social-media-skills/skills. Use to reverse-engineer why a piece of content went viral (or overperformed) — yours or someone else's — and extract the repeatable mechanism to apply to your own content. Run when the user says "why did this go viral," "break down this viral post/video," "reverse engineer," "what made this work," or wants to learn from viral content. Sources the observable signal first (intake, transcript, screenshots, top comments, visible stats — an agent usually can't watch a video from a link) and never fabricates what it…
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `evals/evals.json`, `references/deconstruction-framework.md` and `references/examples.md`).
It sits in Security, covering Reverse engineering and malware and Competitor analysis. The repository describes itself as: 106 social media skills for AI agents - strategy, writing, video, design, platform growth, publishing, and analytics. Works with Claude, Cursor, OpenClaw, Hermes & 40+ agents. The licence is MIT.
When your agent uses it
- Reverse-engineer why a piece of content went viral (or overperformed) — yours
- Someone elses — and extract the repeatable mechanism to apply to your own content
- Says why did this go viral
- Break down this viral post/video
Example prompts
- “why did this go viral,”
- “break down this viral post/video,”
- “reverse engineer,”
- “/viral-reverse-engineering”
Workflow steps
7 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 6e30eeb. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Viral Reverse Engineering loads about 1.9k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 256 tokens; SKILL.md has 797 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from social-media-skills/skills at commit 6e30eeb, republished under its MIT licence (© social-media-skills). 797 words, ~1,865 tokens.
Download SKILL.mdSave it as
.claude/skills/viral-reverse-engineering/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- viral-reverse-engineering
- description
- Use to reverse-engineer why a piece of content went viral (or overperformed) — yours or someone else's — and extract the repeatable mechanism to apply to your own content. Run when the user says "why did this go viral," "break down this viral post/video," "reverse engineer," "what made this work," or wants to learn from viral content. Sources the observable signal first (intake, transcript, screenshots, top comments, visible stats — an agent usually can't watch a video from a link) and never fabricates what it can't see. Reads brand-profile and audience first, deconstructs the piece layer by layer, isolates the real driver, runs a replicability check, extracts the transferable principle, and applies it to the user's niche via the content skills. Mechanism, never a copy; flags non-replicable virality; visible signals only (no WoopSocial analytics). Single-POST teardown only: for the account-level competitive landscape use competitor-analysis; for riding a live trend use trend-jacking.
- metadata.version
- 1.0.0
- license
- MIT
Viral Reverse-Engineering
Most "learn from viral content" advice produces flops, because people copy the surface (the same sound, topic, format) instead of the mechanism (the load-bearing hook, the emotional trigger, the share driver). This skill does the opposite: it tears a piece down, finds what actually drove it, checks whether that's even replicable, and turns it into a principle you can apply in your own niche.
Two commitments:
- Mechanism, not surface. Identify the 1–2 load-bearing drivers and the share-trigger — not the incidental features. Copying noise reproduces noise.
- Honest about luck and survivorship. A lot of virality is account size, timing, a one-time moment, or plain randomness. When success isn't replicable, say so — a false formula is worse than none.
Step 0 — Read the foundation
Load brand-profile.md and audience.md (for the "apply to your niche" step).
Step 1 — Source the content (the step everyone skips)
You usually can't watch a video from a link — platforms are walled, and a fetch returns metadata
at best. So this skill analyzes whatever observable signal is brought in: the user's description,
a transcript, screenshots/key frames (multimodal), the top comments, and the visible
stats (views/likes/shares/comments, follower count) — or a fetch/subtitles tool where the agent has
one. Run the structured intake in references/sourcing-the-content.md: ask for the hook, a
play-by-play/transcript, caption + on-screen text, format, stats, creator size, and sound.
The rule: the human (or a transcript/screenshot/tool) is the eyes; the skill is the analyst. Never fabricate frames or lines you weren't given — analyze what's provided and name the gaps. Also: patterns need multiple examples — one viral post is an anecdote. (WoopSocial has no analytics; work from visible/native signals or pasted data.)
Step 2 — Deconstruct (the teardown)
Tear down each layer: hook, emotional/share driver, retention structure, format/packaging,
topic/angle, share-trigger, distribution factors. One line per layer; don't praise everything. See
references/deconstruction-framework.md.
Step 3 — Isolate the real driver (counterfactual)
For each notable feature, ask "remove this — does it still pop?" Whatever it can't lose without collapsing is a driver; what it can lose is incidental. Usually only 1–2 layers are load-bearing (typically the hook + the emotional/share trigger). Most bad analysis credits the noise.
Step 4 — Identify the share-trigger
Virality = shares, so name why people sent it to someone else: identity/self-expression,
high-arousal emotion (awe/anger/humor/inspiration), social currency, practical value, relatability,
story. A piece with no share-trigger gets views, not virality. See references/why-things-spread.md.
(The top comments are the best evidence here — see references/sourcing-the-content.md.)
Step 5 — Replicability check
Screen for confounds before extracting anything: account-size advantage, luck/variance,
one-time moments, survivorship bias, sample size. If the success is mostly confound,
flag it as non-replicable and don't invent a principle. See references/replicability-and-application.md.
Step 6 — Extract the principle + apply to your niche
State the mechanism in one line, translate it to the user's subject (same mechanism, your topic),
and hand execution to the content skills (hook-writer, tiktok-script, reels-script,
caption-writer, carousel-writer) in the brand voice. Output is "the lever is X; here's X applied
to you" — never a copy. Build a swipe file of recurring patterns over time.
Show full SKILL.md (296 more words)Show less
Quality bar — self-check
- Did I source real input (intake/transcript/screenshots/comments), and not fabricate what I couldn't see — naming the gaps?
- Did I find the mechanism (1–2 real drivers + the share-trigger), not the surface?
- Did the counterfactual rule out incidental features?
- Did I run the replicability check and flag confounds/luck/small-sample honestly?
- Is the output a principle applied to the user's niche, not a copy?
- Did I respect the ethics line (inspiration, not plagiarism/IP theft)?
- Did I use visible/native signals with no analytics claims, and make no virality guarantees?
Edge cases & pushback
- Bare link, nothing else → explain you can't watch the video; run the intake (ask for transcript/screenshots/stats) or use a subtitles/fetch tool if available; don't pretend you saw it.
- Partial input (transcript only, screenshots only) → analyze what's there, name what you can't assess (e.g., pacing/edit, or the spoken layer).
- "Copy it exactly with our product" → mechanism + your own substance, not a surface copy (derivative + IP risk).
- "It was the sound/topic" → counterfactual-test it; usually the hook + trigger were the real lever.
- Huge-account / one-time virality → flag non-replicable; don't extract a false formula.
- One example → anecdote, not a pattern; tear down several to find recurring mechanisms.
- "Guarantee us viral" → no guarantees (luck/distribution); stack the odds via mechanisms.
- No data to judge "viral" → use visible signals; be clear about the limits.
Related skills
brand-profile,audience-research— relevance + the "apply to your niche" step.hook-writer— the most common load-bearing driver;trend-jacking— overlapping "why it spread."tiktok-script,reels-script,caption-writer,carousel-writer— execute the extracted principle.competitor-analysis,analytics-and-reporting(advisory) — broader performance analysis.
References
references/sourcing-the-content.md— how the content gets into context (intake, transcripts, screenshots, comments, tools) + graceful degradation. Start here.references/deconstruction-framework.md— the layer-by-layer teardown + the counterfactual driver test.references/why-things-spread.md— the share-trigger psychology (why people share).references/replicability-and-application.md— survivorship/luck/sample-size honesty; extract + apply; ethics.references/examples.md— worked teardowns, including a non-replicable case.
© social-media-skills, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 6 other files (references) in skills/viral-reverse-engineering of social-media-skills/skills.
- SKILL.md
- evals/evals.json
- references/deconstruction-framework.md
- references/examples.md
- references/replicability-and-application.md
- references/sourcing-the-content.md
- references/why-things-spread.md
Open the folder on GitHubat commit 6e30eeb
Compare with similar skills
Viral Reverse Engineering next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Viral Reverse Engineering this skillsocial-media-skills/skills | 134 | — | ~1.9k | Automated safety check: Pass | MIT | |
| Tiktok Account Auditaronhy/tiktok-agent-skills | 168 | — | ~492 | Automated safety check: Pass | MIT | |
| Suede VideoJasonColapietro/suede-creator-skills | 127 | — | ~4.1k | Automated safety check: Pass | MIT | |
| SEO Content Brief GeneratorAgriciDaniel/claude-seo | 19k | 2 repos | ~2.6k | Automated safety check: Pass | MIT | |
| SEO DataforseoAgriciDaniel/codex-seo | 799 | 2 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Competitor ProfilingNexus-JPF/note-companion | 870 | 4 repos | ~3.5k | Automated safety check: Pass | MIT |
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Questions about Viral Reverse Engineering
What does Viral Reverse Engineering do?
A skill your agent uses to reverse-engineer why a piece of content went viral (or overperformed) — yours or someone else's — and extract the repeatable mechanism to apply to your own content. Viral Reverse Engineering is an agent skill from social-media-skills/skills. Use to reverse-engineer why a piece of content went viral (or overperformed) — yours or someone else's — and extract the repeatable mechanism to apply to your own content.
When should I use Viral Reverse Engineering?
Viral Reverse Engineering fits situations like: reverse-engineer why a piece of content went viral (or overperformed) — yours; someone elses — and extract the repeatable mechanism to apply to your own content; says why did this go viral; break down this viral post/video.
How do I install Viral Reverse Engineering in Claude Code?
Run `npx skills add social-media-skills/skills --skill viral-reverse-engineering -a claude-code`. Or copy the skill folder (skills/viral-reverse-engineering in social-media-skills/skills) into .claude/skills/viral-reverse-engineering in your project. Claude Code loads it when a task matches its description.
How do I install Viral Reverse Engineering in Codex?
Run `npx skills add social-media-skills/skills --skill viral-reverse-engineering -a codex`. Or copy the skill folder (skills/viral-reverse-engineering in social-media-skills/skills) into .agents/skills/viral-reverse-engineering in your project. Codex loads it when a task matches its description.
Can I use Viral Reverse Engineering in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add social-media-skills/skills --skill viral-reverse-engineering -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/viral-reverse-engineering, .gemini/skills/viral-reverse-engineering, .github/skills/viral-reverse-engineering and .opencode/skills/viral-reverse-engineering in your project.
What does Viral Reverse Engineering need to run?
SKILL.md names no scripts, command-line tools or credentials: Viral Reverse Engineering is instructions for the agent only.
Does Viral Reverse Engineering access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Viral Reverse Engineering safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Viral Reverse Engineering use?
Viral Reverse Engineering is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Viral Reverse Engineering use?
About 1.9k tokens (SKILL.md is roughly 7.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.4k tokens, read only when the agent opens those files.
What are the alternatives to Viral Reverse Engineering?
Skills that share tags, products or a category with Viral Reverse Engineering: Tiktok Account Audit (aronhy/tiktok-agent-skills, 168 stars), Suede Video (JasonColapietro/suede-creator-skills, 127 stars), SEO Content Brief Generator (AgriciDaniel/claude-seo, 19k stars) and SEO Dataforseo (AgriciDaniel/codex-seo, 799 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Viral Reverse Engineering?
social-media-skills (a GitHub organization) maintains it in social-media-skills/skills, which has 134 GitHub stars. The repository holds 106 skills in this directory. The repository was last updated on October 1, 2026.
Source: social-media-skills/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.