What does this skill do, and when should you use it?
List Hygiene Monitor is the Email/SEND setup skill in Aaron Marketing Skills for recurring email-list health checks. It cohorts subscribers by last-open or last-click recency, trends hard bounces and spam complaints against benchmarks and a prior baseline, and checks suppression-list growth and leakage. Its main deliverable is a sized, evidence-labeled worklist for re-permission, sunset, and pruning, plus SEND-S and SEND-E sub-item reads. It fits teams running scheduled list reviews, but it does not perform authentication preflight, own consent records, or calculate the full EQS.
Reads a program or list, a typed SEND profile, ESP engagement data, bounce and complaint reports, a prior baseline, and the intended watch cadence. It creates active, cooling, dormant, deep-dormant, and never-engaged or over-365-day cohorts; compares hard-bounce and spam-complaint rates with the stated benchmark and prior run; checks suppression-list growth and opt-out leakage; sizes re-permission, sunset, and prune buckets; labels counts as Measured or Estimated; and produces SEND-S list-hygiene and SEND-E engagement-decay reads as pass, partial, or needs-input. An optional Resend path reads contacts and email events and records KPIs in a measurement ledger.
- A lifecycle marketer sees declining open rates and needs dormant cohorts for a scheduled win-back review.
- An email operations team needs a re-permission, sunset, and prune worklist from its ESP export.
- A deliverability owner wants numeric hard-bounce and complaint deltas against the previous quarter.
- A compliance or operations team needs to detect unsubscribed or suppressed addresses still present on the active sending list.
How do you install this skill?
- Do not treat the worklist as authorization to delete, suppress, or change ESP state; obtain separate confirmation and preserve recoverable records for any external mutation.
- Subscriber-level exports may contain personal data; apply minimization, redaction, and access checks before storing or sharing reports.
- Resolve the version mismatch between skill 18.0.0 and SECURITY.md support for 17.x, and verify all relative paths, scripts, and ESP field mappings.
- This was a static review only; cohorting, trend calculations, and suppression-leakage detection were not executed or reproduced.
- Shell / CLI
- Network access
- Local filesystem
Python 3
Install the repository with npx skills add aaron-he-zhu/aaron-marketing-skills, or use the documented Claude Code flow: /plugin marketplace add aaron-he-zhu/aaron-marketing-skills, followed by /plugin install aaron-marketing@aaron. The skill is located at email/setup/list-hygiene-monitor/SKILL.md. The README does not document a dedicated single-skill install command for this specific skill.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/aaron-he-zhu/aaron-marketing-skills.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/email/setup/list-hygiene-monitor" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Provide the list or program, ESP engagement export, bounce and complaint report, prior baseline, and watch cadence. Example: Watch my list health for [program]. Here is my ESP engagement export and bounce/complaint report — give me the decay cohorts and a prune worklist. Without a prior baseline, the skill should mark the trend NEEDS_INPUT and report only the point-in-time read. After delivery, it asks whether to save the results.
What are this skill's strengths and limitations?
- Produces concrete, sized re-permission, sunset, and prune worklists.
- Requires numeric trend comparisons and distinguishes Measured from Estimated counts.
- Keeps a clear boundary between recurring hygiene, authentication QA, consent ownership, and EQS auditing.
- Works with pasted first-party exports; connectors are optional.
- Requires ESP engagement data, bounce or complaint data, and usually a prior baseline.
- Cannot calculate a trend delta when the baseline is missing.
- Does not compute EQS or enforce S1, S2, N1, or D1 vetoes.
- The supplied source does not document an independent test suite or per-ESP compatibility testing.
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| List Hygiene Monitor this page | 58 · Recommended | ★ 3k | 13d ago | Apache-2.0 |
| Inbox Placement Monitor | 59 · Recommended | ★ 3k | 13d ago | Apache-2.0 |
| Reactivation Specialist | 57 · Use with care | ★ 3k | 13d ago | Apache-2.0 |
| Email Deliverability Preflight | 61 · Recommended | ★ 3k | 13d ago | Apache-2.0 |
| B2B Cold Outbound Sequencer | 57 · Use with care | ★ 3k | 13d ago | Apache-2.0 |
Unlike deliverability-qa, this skill performs recurring between-send list-decay monitoring rather than a one-time authentication preflight. Unlike consent-registry, it checks suppression drift and leakage but does not own the consent or suppression record. Unlike email-quality-auditor, it supplies SEND-S/E evidence and an action worklist rather than calculating EQS or issuing the final gate verdict.
How did FollowSkills review this skill?
The skill treats exports and subscriber lists as untrusted data, uses keyless first-party inputs, separates reads, writes, promotions, and scope boundaries, and asks before saving memory. However, it does not itself specify redaction, minimization, or access controls for subscriber-level sensitive data, and confirmation, rollback, and recovery for cleanup or suppression actions are incomplete; 7 points are deducted.
Required inputs, cohorting, NEEDS_INPUT handling for missing baselines, abnormal-trend escalation, and leakage handoff are described coherently. However, the referenced scripts, shared files, and ESP schemas are not verified within this skill, and no tests or diagnostic execution evidence cover its key paths; 12 points are deducted, with the static cap keeping the score at or below 10.
Triggers, audience, four email profiles, inputs, outputs, exclusions, and next-skill routing are clearly stated, and manual exports avoid requiring overseas connectivity. However, Chinese-language support is limited mainly to labels and brief text, while ESP field mapping and mainland-China environment boundaries lack evidence; 4 points are deducted.
The documentation has strong structure, metadata, quick starts, contract, data sources, instructions, handoff, limitations, references, next-skill guidance, versioning, and an Apache-2.0 license. Maintenance ownership, update path, changelog, and compatibility governance remain unclear; additionally, SECURITY.md says 17.x is the supported line while the skill declares 18.0.0, so 4 points are deducted.
The promised output is concrete: engagement cohorts, trend comparisons, suppression-drift checks, and actionable re-permission, sunset, and prune worklists with count and measurement labels. No representative execution output or skill-specific validation is supplied, so correctness, field handling, and direct actionability still require review; 9 points are deducted, with the static cap keeping the score at or below 7.
The skill supplies explicit thresholds, cohort bands, baseline rules, input requirements, and a checklist, while the README and repository tests show general architecture and audit validation. It provides no skill-specific key-path tests, real execution records, or independent corroboration, and nothing was executed in this review; 6 points are deducted, with the static cap keeping the score at or below 5.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →