Auto-Company is a software system that runs a recurring team of AI agents on a personal computer, where the agents plan work, make decisions, write code, deploy applications, and handle marketing. It is intended for autonomous product development on Windows, Linux, or macOS, using command-line agent tools and a local dashboard to track cycles and results. The catalogue entries are skills, agents, settings, and instructions that support this automated workflow.
Borrowing it
Nothing to install: this file belongs to MaxMiksa/Auto-Company. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/MaxMiksa/Auto-Company/main/.claude/skills/email-sequence/SKILL.mdgit clone --depth 1 https://github.com/MaxMiksa/Auto-CompanyWrote 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/maxmiksa/auto-company/email-sequence)<a href="https://agentmods.dev/skills/maxmiksa/auto-company/email-sequence"><img src="https://agentmods.dev/badge/skills/maxmiksa/auto-company/email-sequence/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/maxmiksa/auto-company/email-sequence"><img src="https://agentmods.dev/badge/skills/maxmiksa/auto-company/email-sequence.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 | $0.00084 | $0.02055 |
| Opus 5.5 | $0.00034 | $0.00822 |
| Sonnet 5.5 | $0.00017 | $0.00411 |
| Haiku 4.5 | $0.00008 | $0.00205 |
Grade A, and why
email-sequence 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 — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Email Sequence Design
You are an expert in email marketing and automation. Your goal is to create email sequences that nurture relationships, drive action, and move people toward conversion.
Initial Assessment
Check for product marketing context first:
If .claude/product-marketing-context.md exists, read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Before creating a sequence, understand:
-
Sequence Type
- Welcome/onboarding sequence
- Lead nurture sequence
- Re-engagement sequence
- Post-purchase sequence
- Event-based sequence
- Educational sequence
- Sales sequence
-
Audience Context
- Who are they?
- What triggered them into this sequence?
- What do they already know/believe?
- What's their current relationship with you?
-
Goals
- Primary conversion goal
- Relationship-building goals
- Segmentation goals
- What defines success?
Core Principles
1. One Email, One Job
- Each email has one primary purpose
- One main CTA per email
- Don't try to do everything
2. Value Before Ask
- Lead with usefulness
- Build trust through content
- Earn the right to sell
3. Relevance Over Volume
- Fewer, better emails win
- Segment for relevance
- Quality > frequency
4. Clear Path Forward
- Every email moves them somewhere
- Links should do something useful
- Make next steps obvious
Email Sequence Strategy
Sequence Length
- Welcome: 3-7 emails
- Lead nurture: 5-10 emails
- Onboarding: 5-10 emails
- Re-engagement: 3-5 emails
Depends on:
- Sales cycle length
- Product complexity
- Relationship stage
Timing/Delays
- Welcome email: Immediately
- Early sequence: 1-2 days apart
- Nurture: 2-4 days apart
- Long-term: Weekly or bi-weekly
Consider:
- B2B: Avoid weekends
- B2C: Test weekends
- Time zones: Send at local time
Subject Line Strategy
- Clear > Clever
- Specific > Vague
- Benefit or curiosity-driven
- 40-60 characters ideal
- Test emoji (they're polarizing)
What ships with it
3 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.
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 Changed · +4 lines 1c91bd9d36e4
- 1mo ago First seen · 307 lines · 84 tokens per session scan A d1abc04bc58e
email-sequence is a skill published in the GitHub repository MaxMiksa/Auto-Company (3,141 stars, last pushed 4d ago), licensed MIT. It adds 84 tokens to every session and 2,055 once invoked, about $0.0003 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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