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 Ertinox7711/SGRR-AGI-V2 --skill create-viral-contentgit clone --depth 1 https://github.com/Ertinox7711/SGRR-AGI-V2Wrote 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/ertinox7711/sgrr-agi-v2/create-viral-content)<a href="https://agentmods.dev/skills/ertinox7711/sgrr-agi-v2/create-viral-content"><img src="https://agentmods.dev/badge/skills/ertinox7711/sgrr-agi-v2/create-viral-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/ertinox7711/sgrr-agi-v2/create-viral-content"><img src="https://agentmods.dev/badge/skills/ertinox7711/sgrr-agi-v2/create-viral-content.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00050 | $0.03838 |
| Opus 5 | $0.00025 | $0.01919 |
| Sonnet 5 | $0.00010 | $0.00768 |
| Haiku 4.5 | $0.00005 | $0.00384 |
Grade A, and why
create-viral-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 3d 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 — 440 lines — stays where its author put it; the contents beside it link to each section on GitHub.
⚠️ BEFORE USING THIS SKILL: Review all files in the
resources/directory. These contain AI tell catalogs, platform templates, refinement protocols, and 40-source research basis required for proper skill execution.
Research Basis
This skill synthesizes findings from 40 documented research sources:
- BuzzSumo: 100M headlines study → optimal length is 11 words/65 characters
- Outbrain: Negative superlatives outperform positive by 63%
- Netflix: 82% of browsing time on thumbnails, 1.8s decision window
- Face Psychology: +35-50% CTR with faces in thumbnails
- A/B Testing Research: 30-40% CTR improvement over time
Full statistics in resources/research-statistics.md.
Create Viral Content
Make your posts spread. This skill turns forgettable drafts into content that gets shares, comments, and action.
Core Principle: The Deliberative Refinement Loop
Good content doesn't come from one pass. You attack it, fix it, attack again:
- Generate initial draft
- Attack it from audience perspectives
- Identify AI tells and weak points
- Refine with human voice
- Repeat until unbreakable
The Anatomy of Viral Content
Hook Architecture (First 2 Seconds)
Pattern: Prediction + Stakes
"I think [CONCEPT] is the [YEAR] [CATEGORY] that [OUTCOME]."
Example: "I think deliberative refinement is the 2026 prompt technique that matters most."
Why it works:
- "I think" = personal conviction, not corporate announcement
- Year = creates FOMO and timeframe
- Category = helps reader self-identify
- Outcome = stakes that matter
Pattern: Tribal Identity Split
"[TECHNIQUE] separates [WINNERS] from [EVERYONE ELSE]."
Example: "This separates serious builders from prompt tourists."
Why it works:
- Creates in-group/out-group
- Reader immediately picks a side
- Ego investment drives engagement
Pattern: Before/After Compression
"What used to require [OLD COMPLEXITY] now [NEW SIMPLICITY]."
Example: "What used to need 12 models chained together now takes one."
What ships with it
11 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.
- marketplace.json 1.7 KB
- README.md 4.1 KB
- resources/ai-tells.md 9.1 KB
- resources/humanize-integration.md 4.4 KB
- resources/platform-templates.md 9.4 KB
- resources/refinement-protocol.md 7.9 KB
- resources/research-statistics.md 4.2 KB
- resources/thumbnail-checklist.md 4.8 KB
- resources/title-formulas.md 6.0 KB
- resources/viral-thumbnails.md 14 KB
- resources/viral-titles.md 14 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.
- 3d ago First seen · 440 lines · 0 tokens per session scan A 342020b463d6
create-viral-content is a skill published in the GitHub repository Ertinox7711/SGRR-AGI-V2 (1 stars, last pushed 4d ago), licensed MIT. It adds 50 tokens to every session and 3,838 once invoked, about $0.0003 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 2026-09-09.
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