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 coleschaffer/copywritingskills-rmbc --skill reengagement-sequencegit clone --depth 1 https://github.com/coleschaffer/copywritingskills-rmbcWrote 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/coleschaffer/copywritingskills-rmbc/reengagement-sequence)<a href="https://agentmods.dev/skills/coleschaffer/copywritingskills-rmbc/reengagement-sequence"><img src="https://agentmods.dev/badge/skills/coleschaffer/copywritingskills-rmbc/reengagement-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/coleschaffer/copywritingskills-rmbc/reengagement-sequence"><img src="https://agentmods.dev/badge/skills/coleschaffer/copywritingskills-rmbc/reengagement-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 | $0.00038 | $0.01861 |
| Opus 5 | $0.00019 | $0.00931 |
| Sonnet 5 | $0.00008 | $0.00372 |
| Haiku 4.5 | $0.00004 | $0.00186 |
Grade A, and why
reengagement-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 10d 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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
reengagement-sequence
Purpose
Generate a reengagement email sequence (3-5 emails) that reactivates inactive subscribers or cleanly removes them from the list. Inactive subscribers hurt deliverability, inflate costs, and drag down open rates — but many are recoverable with the right approach. This sequence gives them compelling reasons to re-engage, escalates with an exclusive offer, and ends with a clear sunset warning that either wakes them up or lets you remove them cleanly. RMBC applies as re-persuasion architecture: Research identifies why they disengaged, Mechanism reminds them what makes you different, Brief structures the win-back arc, Copy executes with honesty and value.
Inputs
| Input | Required | Description |
|---|---|---|
brand_name |
Yes | Brand or sender name they originally subscribed to |
target_audience |
Yes | Who the subscriber was — demographics, original interest, likely pain points |
key_value_prop |
Yes | The core reason they subscribed — what value they were expecting |
win_back_offer |
Yes | Exclusive offer for re-engagement — discount, free resource, or special access |
sequence_length |
No | Number of emails: 3, 4, or 5 (default: 4) |
inactivity_threshold |
No | How long they've been inactive — used for copy calibration (default: 90 days) |
Execution Protocol
Step 1 — Load Framework Context
Read rmbc-context/SKILL.md to load RMBC framework definitions. Reengagement sequences re-deploy RMBC against a cooled audience — these subscribers once found you valuable enough to opt in. The job is reminding them why, delivering fresh value, and forcing a decision: re-engage or unsubscribe.
Step 2 — Map the Reengagement Arc
| Role | Emotional Lever | Approach | |
|---|---|---|---|
| 1 — "We Miss You" | Acknowledge absence, re-introduce value | Nostalgia + curiosity | Warm, personal, non-pushy. Remind them why they subscribed. Show what they've missed. |
| 2 — Value Reminder | Deliver a high-value piece of content | Proof you're still worth their attention | Best recent content, tip, or insight — demonstrate value immediately |
| 3 — Exclusive Offer | Present the win-back incentive | Feeling special, exclusive access | Offer available only to returning subscribers — make them feel valued, not desperate |
| 4 — "Last Chance" | Final nudge with clear consequences | Loss aversion + clarity | "We don't want to see you go, but we only want to email people who want to hear from us" |
| 5 — Sunset Warning | Administrative: unsubscribe notice | Clean break | "We're removing you from our list in 48 hours unless you click below to stay" |
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.
- 10d ago First seen · 153 lines · 38 tokens per session scan A 6c096acfd114
reengagement-sequence is a skill published in the GitHub repository coleschaffer/copywritingskills-rmbc (30 stars, last pushed 5mo ago), licensed MIT. It adds 38 tokens to every session and 1,861 once invoked, about $0.0002 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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