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-instagram-reelsgit 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-instagram-reels)<a href="https://agentmods.dev/skills/vyralcontent/content-skills/viral-instagram-reels"><img src="https://agentmods.dev/badge/skills/vyralcontent/content-skills/viral-instagram-reels/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-instagram-reels"><img src="https://agentmods.dev/badge/skills/vyralcontent/content-skills/viral-instagram-reels.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 | $0.00196 | $0.02762 |
| Opus 5 | $0.00098 | $0.01381 |
| Sonnet 5 | $0.00039 | $0.00552 |
| Haiku 4.5 | $0.00020 | $0.00276 |
Grade A, and why
viral-instagram-reels 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 Instagram Reels
Help the user plan, write, and diagnose Instagram Reels specifically. The mechanics here are different from TikTok and Shorts: sends drive cold reach, originality is enforced, and Trial Reels let you test a Reel on non-followers before it touches your follower feed. This skill encodes the Reels-only rules that change what a good Reel looks like today. It does not predict virality. It stacks the odds and tells you what to optimize for on this surface.
For cross-platform hook craft, see viral-hooks. For ideation systems, see
viral-short-form-ideas. For deep caption work, see viral-captions-and-ctas.
Use this skill when the question is Reels-specific.
Operating principles (read these first, apply throughout)
- Sends per reach is the metric that buys you new audience. A DM share tends to count roughly three to five times more than a like when Instagram decides whether to push a Reel to non-followers. Design the Reel and the CTA to earn a share, not a like.
- Watch time is still the biggest single signal. The first three seconds is the public inflection point. Drop-off before three seconds reads as a failed hook and caps the seed test.
- Test cold before you commit. If the Reel is meant to reach non-followers and you have over 1,000 followers, default to Trial Reels first. A flop never touches your follower feed metrics. A winner gets a confirmed cold signal before you publish to everyone.
- Originality is enforced, not encouraged. Reels that look like reposts are cut from cold distribution. Strip third-party watermarks, shoot or substantially edit your own footage, and keep the rolling 30-day window majority-original.
- Captions and on-screen text are the SEO surface. Hashtags are not. Mosseri said directly that hashtags do not improve reach. Three to five relevant ones is the working ceiling. Put the keywords in the caption and on screen instead.
- Reels is a discovery surface, not a follower surface. Your existing followers see only a fraction of your Reels. Plan every Reel for someone who has never heard of you.
- Honest framing. Pattern-matching, not prediction. Say "this tends to lift sends" and explain why. Never promise a Reel will go viral.
What ships with it
12 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/insights-readout.md 2.6 KB
- assets/reels-hook-checklist.md 2.2 KB
- assets/reels-script-template.md 3.5 KB
- assets/trial-reels-decision.md 2.4 KB
- references/caption-and-search.md 6.7 KB
- references/diagnose-flop.md 7.0 KB
- references/edits-app.md 4.8 KB
- references/insights.md 7.2 KB
- references/originality-and-audio.md 7.0 KB
- references/reels-hook.md 5.3 KB
- references/sends-playbook.md 5.7 KB
- references/trial-reels.md 5.0 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 · 196 tokens per session scan A bef61d6b5ccf
viral-instagram-reels is a skill published in the GitHub repository vyralcontent/content-skills (106 stars, last pushed 2mo ago), licensed MIT. It adds 196 tokens to every session and 2,762 once invoked, about $0.0010 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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