Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add vyralcontent/content-skills --skill viral-tiktok-contentgit clone --depth 1 https://github.com/vyralcontent/content-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vyralcontent/content-skills/viral-tiktok-content)<a href="https://agentmods.dev/skills/vyralcontent/content-skills/viral-tiktok-content"><img src="https://agentmods.dev/badge/skills/vyralcontent/content-skills/viral-tiktok-content/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vyralcontent/content-skills/viral-tiktok-content"><img src="https://agentmods.dev/badge/skills/vyralcontent/content-skills/viral-tiktok-content.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00158 | $0.02668 |
| Opus 5 | $0.00079 | $0.01334 |
| Sonnet 5 | $0.00032 | $0.00534 |
| Haiku 4.5 | $0.00016 | $0.00267 |
Grade A, and why
viral-tiktok-content scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Viral TikTok content
Help the user write, shape, or fix content for TikTok specifically. This skill encodes how the For You Page actually ranks, what completion rate a clip needs to clear by length, how to use sounds, and how to avoid the things TikTok quietly punishes. It does not predict virality. It stacks the odds.
For cross-platform hook archetypes, see also viral-hooks. For Reels or
Shorts, see viral-instagram-reels and viral-youtube-shorts. For ideation,
see viral-short-form-ideas. For caption craft and CTAs, see
viral-captions-and-ctas.
Operating principles (read these first, apply throughout)
- The FYP is an interest graph, not a follower graph. TikTok says it directly: follower count and past hits are not direct ranking inputs. Every video is re-tested on its own metadata, sound, and early signals.
- Completion rate is the gate. Watch time and completion outweigh likes. Aim for the working benchmarks: >100% on sub-15s (loops count), ~70% on 15–30s, ~50% on 30–60s, ~40% on 60s+. Below the gate, distribution stalls.
- The first 3 seconds is the whole hook. Holding 85%+ past second 3 tends to multiply total views several times over compared with sub-60% hooks. No logos, "hey guys welcome back," or intro animation.
- Saves and shares outweigh likes. Saves read as future intent, shares as social proof. Build for "send this to a friend" or "I'll need this later."
- Distribution is test-then-expand. New uploads get shown to a small lookalike cohort first. Strong early signals push the video wider, weak ones park it. Stale videos can re-enter testing, so don't delete underperformers.
- Honesty about prediction. Say what tends to work and why. Never promise FYP placement. Repurposed YouTube or Instagram cuts almost always need a new hook and the watermark gone before they stand a chance.
What ships with it
13 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/hook-checklist.md 2.1 KB
- assets/long-tiktok-template.md 4.5 KB
- assets/shop-video-template.md 4.2 KB
- assets/sound-tracker.md 2.4 KB
- assets/tiktok-script-template.md 3.1 KB
- references/algorithm.md 5.2 KB
- references/anti-patterns.md 5.9 KB
- references/native-features.md 5.9 KB
- references/retention-math.md 4.9 KB
- references/script-structure.md 6.0 KB
- references/shop-and-monetization.md 6.3 KB
- references/sounds.md 4.8 KB
- references/tiktok-hooks.md 5.4 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 181 lines · 158 tokens per session scan A 526b97eb6eef
viral-tiktok-content is a skill published in the GitHub repository vyralcontent/content-skills (103 stars, last pushed 2mo ago), licensed MIT. It adds 158 tokens to every session and 2,668 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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