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 Frontal-so/outbound-skills --skill re-engagementgit clone --depth 1 https://github.com/Frontal-so/outbound-skillsWrote 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/frontal-so/outbound-skills/re-engagement)<a href="https://agentmods.dev/skills/frontal-so/outbound-skills/re-engagement"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/re-engagement/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/frontal-so/outbound-skills/re-engagement"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/re-engagement.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 | $0.00119 | $0.00784 |
| Opus 5 | $0.00060 | $0.00392 |
| Sonnet 5 | $0.00024 | $0.00157 |
| Haiku 4.5 | $0.00012 | $0.00078 |
Grade A, and why
re-engagement 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 11d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Re-Engagement Email Writing
You write emails that revive cold leads, closed-lost deals, and prospects who went dark. These are NOT follow-ups within an active sequence -- these target leads from weeks or months ago.
Process
- Understand the history -- When was last contact? What was discussed? Why did they go cold?
- Identify the new angle -- What has changed since then? (new feature, new data, new trigger)
- Draft re-engagement -- No-oriented question, very soft CTA, acknowledge the gap
Reference
Read {SKILL_BASE}/resources/templates/email-templates-library.md for re-engagement templates (#31-34): no-oriented questions, closed-lost reactivation, and ramp re-engagement.
Re-Engagement Types
1. No-Oriented Question (Rebook Demos)
For prospects who booked but did not convert. Use "no-oriented" questions that are easy to say no to (which paradoxically gets more replies).
2. Closed-Lost Reactivation
For deals that were lost. Reference the original objection and what has changed since.
3. Ramp Re-Engagement
For leads from old sequences. New angle, new trigger, very soft ask for the right person.
Key Principles
- Acknowledge the gap -- Do not pretend the previous interaction did not happen
- Lead with what changed -- New feature, new data, new case study, market shift
- No-oriented questions work -- "Would it be crazy to reconnect?" gets more replies than "Want to chat?"
- Reference their words -- If they gave an objection, name it: "You mentioned X was the blocker"
- Very soft CTAs -- "Still relevant?" or "Worth another look?" not "Book a call"
Examples
Example 1: No-Oriented Question (Rebook)
Subject: quick question
{{firstName}},
Would it be crazy to reconnect?
I know we talked {{timeframe}} ago about {{topic}}.
We've since launched {{new_feature}} which directly addresses the {{objection}} concern.
Still relevant?
Example 2: Closed-Lost Reactivation
Subject: since we last talked
{{firstName}},
When we talked in {{month}}, you mentioned {{objection}} was the blocker.
Since then, we've {{specific_improvement}} -- {{similar_company}} saw {{result}} after making the switch.
Worth another look?
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.
- 11d ago First seen · 88 lines · 119 tokens per session scan A 248ccbdad274
re-engagement is a skill published in the GitHub repository Frontal-so/outbound-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 119 tokens to every session and 784 once invoked, about $0.0006 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 2026-08-31.
Other skills, from other repositories
audience-icp-filter
Filter an existing audience or lead list against your ICP and split it into ready-to-sequence segments. Use when someone already has a list of people — an audience in their sales tool, a CSV or CRM export, event or webinar attendees, registrants, a Sales Navigator import, a newsletter or community export — and wants…
team-performance-dashboard
Generate your Team Performance Dashboard from your La Growth Machine data: a head-of-sales cockpit that ranks each sender (rep) on reply rate, your success event (signups/meetings/deals) and conversion, surfaces hot leads going cold, and turns your best reps' campaigns into a coaching playbook for the rest. Pulls only…
weekly-performance-advisor
Generate your Weekly Performance Advisor dashboard from your La Growth Machine data: a two-tab cockpit (To do + Weekly performance) that flags campaigns to fix, sorts replies by urgency, and tracks reply volume week over week. It pulls only YOUR live LGM data, scores each running campaign against baked 3-zone…
objection-analyzer
Find out which objections your outbound gets, how well your team handled them, and what to say next time. Use whenever the user wants to analyze the objections in their replies, rank the most frequent ones, know how to handle a specific objection, coach reps on their objection answers, build an objection playbook or…
sales-nav-search-builder
Generate a precise LinkedIn Sales Navigator search URL from a natural-language ICP description — for sales prospecting, outbound outreach, lead generation, and B2B targeting. Use whenever the user asks for a Sales Nav URL, a LinkedIn search URL, an outbound prospecting query, a search for a persona or role, wants to…
reply-draft-assistant
Handle replies to your cold outreach end to end — classify each response, draft the right answer from the full conversation, and send it through La Growth Machine after you approve. Use any time the user has replies to handle: their LGM inbox ("who do I need to reply to?"), a campaign's replies, or a pasted thread.…