Dripcampaignskill
Skill aiskillstore/marketplace/skills/sequenzy/dripcampaignskill
Use when Codex, Hermes, OpenClaw, Claude Code, Cowork, or another AI agent needs to plan, review, implement, audit, or improve email work focused on time-based nurture streams, branching logic, lead scoring hooks, and conversion analysis. Triggers include requests about nurture sequence planning, lead scoring hooks, drop-off analysis, sales handoffs, and timed education streams.From its SKILL.md
npx -y skills add aiskillstore/marketplace --skill dripcampaignskillAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
3.1 KB, 525 tokens by cl100k_base, as published. Nobody here has run it
Drip Campaign Skill
Design nurture as progressive context, not a pile of delayed emails. Each step should advance readiness or route the contact elsewhere.
Fit Check
- Primary lens: time-based nurture streams, branching logic, lead scoring hooks, and conversion analysis.
- Common request signals: nurture sequence planning, lead scoring hooks, drop-off analysis, sales handoffs, and timed education streams.
- Default posture: Design nurture as progressive context, not a pile of delayed emails. Each step should advance readiness or route the contact elsewhere.
- Useful output family: drip maps, nurture briefs, branch logic tables, scoring hooks, drop-off diagnoses, and conversion-focused rewrite plans.
- Production boundary: separate recommendation from execution.
- Evidence boundary: say which source material supports the recommendation.
- Review boundary: identify the human owner for risky changes.
- Data boundary: do not assume missing fields, consent, or suppression state.
- Platform boundary: describe provider-specific steps in operational language.
- Measurement boundary: define what success or recovery will look like.
Use This For
time-based nurture streams, branching logic, lead scoring hooks, and conversion analysis.
Avoid Using It For
Generic email advice with no audience, platform, lifecycle, evidence, or approval context.
Procedure
- Define the campaign entry moment and the recipient's current intent, source, and awareness level.
- Map the sequence promise across time: what the contact should understand, believe, or do after each message.
- Set delays and branches based on decision points, not arbitrary spacing.
- Add lead scoring or qualification hooks only when sales, onboarding, or support will act on them.
- Audit drop-off by message, branch, source, segment, and CTA to find where readiness stalls.
- Recommend edits that improve sequence logic before rewriting every email.
Acceptance Checks
- Every email has a distinct job in the nurture path.
- Branching criteria are measurable and available in the platform.
- Sales or product handoff thresholds are explicit.
- The sequence has exits for conversion, disqualification, inactivity, and suppression.
- Performance review separates timing, audience fit, offer, and copy issues.
Output Pattern
Return drip maps, nurture briefs, branch logic tables, scoring hooks, drop-off diagnoses, and conversion-focused rewrite plans. Keep recommendations concrete. Separate analysis from live-system actions, and require explicit approval before sending email, importing contacts, changing DNS, altering suppression rules, or editing production automations.
What ships with it: 3 files
11.0 KB alongside SKILL.md
agents/
- openai.yaml281 B
references/
- operating-checklist.md1.3 KB
- skill-report.json9.4 KB