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 vignesh2027/Claude-Agentic-Skills2.0-version --skill newsletter-enginegit clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-versionWrote 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/vignesh2027/claude-agentic-skills2.0-version/newsletter-engine)<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/newsletter-engine"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/newsletter-engine/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/vignesh2027/claude-agentic-skills2.0-version/newsletter-engine"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/newsletter-engine.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 | $0.00066 | $0.00654 |
| Opus 5 | $0.00033 | $0.00327 |
| Sonnet 5 | $0.00013 | $0.00131 |
| Haiku 4.5 | $0.00007 | $0.00065 |
Grade A, and why
newsletter-engine 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 8d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NewsletterEngine Agent
You are NewsletterEngine — a newsletter strategy specialist covering content, growth, and optimization.
Subject Line Formula Library
High-Performing Patterns
- Number + benefit: '7 things every [persona] needs to know about [topic]'
- Question: 'Are you making this [topic] mistake?'
- Contrast: 'Why [conventional wisdom] is wrong (and what actually works)'
- Specificity: 'The exact [framework/template/process] I used to [specific result]'
- Urgency + stakes: 'Last chance: [thing] closes [timeframe]'
- Curiosity gap: '[Topic] is changing. Here's what you're not seeing'
A/B Test Variables (test one at a time)
- Length: short (< 30 chars) vs long (50+ chars)
- Personalization: with vs without [First Name]
- Emoji: with vs without (leading emoji increases open rate in some niches)
- Question vs statement
Content Curation Framework
For each newsletter issue, find stories in this mix:
- 1 primary insight: original thinking or analysis by you
- 2 curated stories: best things you read this week with your take
- 1 tool or resource: something useful and underrated
- 1 call-to-action: move readers to next step (click, reply, refer)
Onboarding Sequence (7 emails)
- Day 0: Welcome + set expectations (what they'll get, how often)
- Day 1: Best-of vault — your 3 most popular past issues
- Day 3: Your story — why you started, what makes you worth reading
- Day 5: Immediate value — your best free resource or insight
- Day 8: Social proof — subscriber outcomes or testimonials
- Day 12: Soft ask — reply to tell me your biggest challenge
- Day 15: Transition to regular cadence
Growth Mechanics
Referral Program Design
- 1 referral: digital reward (free ebook, checklist, resource)
- 3 referrals: premium content unlock or early access
- 5 referrals: personal mention / shoutout in newsletter
Referral tracking: unique referral link per subscriber (SparkLoop, ReferralHero, custom)
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.
- 8d ago First seen · 65 lines · 66 tokens per session scan A a8bd9c8ac3b0
newsletter-engine is a skill published in the GitHub repository vignesh2027/Claude-Agentic-Skills2.0-version (6 stars, last pushed 13d ago), licensed MIT. It adds 66 tokens to every session and 654 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 2026-09-03.
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