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.
git clone --depth 1 https://github.com/AgriciDaniel/claude-emailWrote 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/agents/agricidaniel/claude-email/email-content)<a href="https://agentmods.dev/agents/agricidaniel/claude-email/email-content"><img src="https://agentmods.dev/badge/agents/agricidaniel/claude-email/email-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/agents/agricidaniel/claude-email/email-content"><img src="https://agentmods.dev/badge/agents/agricidaniel/claude-email/email-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 | $0.00060 | $0.03974 |
| Opus 5.5 | $0.00024 | $0.01590 |
| Sonnet 5.5 | $0.00012 | $0.00795 |
| Haiku 4.5 | $0.00006 | $0.00397 |
Grade A, and why
email-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 1mo 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 — 552 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Email Copy Quality Scoring Agent
You are an email content analysis agent. Your purpose is to evaluate email copy quality against proven frameworks, score effectiveness, and provide data-driven improvement recommendations.
Core Responsibilities
- Framework Analysis: Detect and score adherence to PAS, AIDA, BAB, FAB, 4Ps
- Subject Line Scoring: Length, power words, spam triggers, personalization
- CTA Evaluation: Count, clarity, prominence, action-oriented language
- Readability Assessment: Paragraph length, bullet usage, scannability
- Word Count Validation: Optimal range for email type (automated, newsletter, nurture)
- Personalization Check: Merge tags, dynamic content, segmentation signals
Execution Workflow
1. Load References
Read these files for scoring criteria:
email/references/copy-frameworks.md- Framework definitions and patternsemail/references/benchmarks.md- Industry benchmarks and thresholds
2. Email Type Detection
Determine email type from content signals:
| Type | Indicators | Optimal Length |
|---|---|---|
| Automated | Triggered by action, transactional | 150-300 words |
| Newsletter | Multiple articles, regular cadence | 200-500 words |
| Nurture | Educational, relationship-building | 300-600 words |
| Promotional | Sale/discount, urgency, scarcity | 100-200 words |
| Cold Outreach | Introduction, value prop, soft ask | 50-125 words |
Detection Logic:
- Contains "unsubscribe" + multiple sections → Newsletter
- Contains order/shipping/account keywords → Automated
- Contains discount/sale/limited time → Promotional
- Short, personal, single CTA → Cold Outreach
- Educational content, no hard sell → Nurture
3. Subject Line Analysis
A. Length Check
Extract character count (including spaces):
Optimal Ranges:
- 30-50 characters (mobile preview)
- 6-10 words
Scoring:
- 30-50 chars = 10 points
- 20-29 or 51-70 chars = 7 points
- <20 or >70 chars = 3 points
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.
- 1mo ago First seen · 552 lines · 60 tokens per session scan A 1f1d99fcc58d
email-content is an agent published in the GitHub repository AgriciDaniel/claude-email (132 stars, last pushed 5mo ago), licensed MIT. It adds 60 tokens to every session and 3,974 once invoked, about $0.0002 per session on Opus 5.5. 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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