aaron-marketing-skills is a collection of 120 AI-agent skills covering marketing work such as brand narrative, search optimization, social media, email, advertising, influencer campaigns, and launches. Marketers and agent users can install it as a plugin, use its portable skills, or run its described bot team. The catalogue entries are components of this marketing workflow.
Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add aaron-he-zhu/aaron-marketing-skills/plugin install aaron-marketingWrote 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/aaron-he-zhu/aaron-marketing-skills/list-segment-builder)<a href="https://agentmods.dev/skills/aaron-he-zhu/aaron-marketing-skills/list-segment-builder"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/list-segment-builder/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/aaron-he-zhu/aaron-marketing-skills/list-segment-builder"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/list-segment-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
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 | $0.00157 | $0.03120 |
| Opus 5 | $0.00078 | $0.01560 |
| Sonnet 5 | $0.00031 | $0.00624 |
| Haiku 4.5 | $0.00016 | $0.00312 |
Grade A, and why
list-segment-builder 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
List Segment Builder
Turns the user's own list/CRM/GA4/ecommerce export into behavioral segments (engaged-90d, cart-abandoners), attribute and RFM tiers, lifecycle-stage segments (new, active, lapsed, win-back), and a suppression list (unsubscribed, hard-bounced, spam-complained, consent-withdrawn). It defines who each segment is and who must never be mailed — email-creative-builder and email-sequence-designer then compose for those segments; this skill does not send, design flows, or score the program.
Quick Start
Build email segments from my list export: [path]. Goal is retention. ESP export attached.
Make engaged-90d, lapsed, and cart-abandoner segments from my ecommerce + ESP export, and give me the suppression list. [CSV]
Map my list to RFM tiers and lifecycle stages so I can reuse the same audiences across every campaign. [CRM export]
Skill Contract
Expected output: a segment map in four buckets — (1) behavioral segments grouped by activity (opened/clicked recency, cart-abandon, browse-abandon), (2) attribute + RFM tiers (recency/frequency/monetary from the user's own order data), (3) lifecycle-stage segments (new → active → at-risk → lapsed → win-back), and (4) a suppression list (unsubscribed, hard-bounced, spam-complained, consent-withdrawn) — each segment named with a size labeled Measured (counted from an exported column) or Estimated (inferred, method stated), informing the SEND E (Engagement/targeting) dimension, plus the standard handoff summary.
- Reads: the user's own list/CRM CSV (subscribe date, last-open/last-click date, opt-in status), ESP campaign export (opens/clicks per subscriber), GA4/ecommerce export (order recency, frequency, monetary value); the program goal (promo / retention / cold); and versioned consent/suppression snapshots from the consent-registry (
memory/consent/). Member-level joins use host-issued opaquesubject_refvalues; raw addresses stay transient. - Writes: a user-facing segment map and reusable summary to
memory/email/list-segment-builder/. - Promotes: the segment names, the lifecycle-stage map, the suppression-rule set, and any missing export to
memory/hot-cache.mdandmemory/open-loops.md; propose durable segment definitions as pending-decision items (never write consent records — the registry ownsmemory/consent/). - Done when: each segment is named, grounded in an exported column, and frozen as a definition version/hash with an evaluation time; every size is labeled Measured or Estimated; RFM tiers use the user's own recency/frequency/monetary fields; the suppression list reconciles against named consent/suppression snapshot refs (or flags NEEDS_INPUT where no current record exists); raw addresses appear in no saved artifact; and the SEND E relevance of each bucket is noted.
- Primary next skill: email-creative-builder to compose for the top segment, or email-sequence-designer to design a flow per lifecycle stage.
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 Changed · +2 lines 57339f08db92
- 13d ago First seen · 88 lines · 157 tokens per session scan A 3149ac68e5e3
list-segment-builder is a skill published in the GitHub repository aaron-he-zhu/aaron-marketing-skills (2,767 stars, last pushed today), licensed Apache-2.0. It adds 157 tokens to every session and 3,120 once invoked, about $0.0008 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.
Other skills, from other repositories
geo-visibility-check
One-shot GEO audit: does your brand appear in Claude, ChatGPT, and Gemini answers for the buyer questions that matter? Runs a prompt panel through the engines with citation tracing and reports per-prompt verdicts, who wins instead, and which sources the answers come from.
geo-optimizer-skill
Run geo audit first. It scores the site 0–100 across 8 categories and generates a prioritized action list.
geo-loop
Run one bounded eGEOagents loop iteration over a workspace domain - read the charter and fresh collector data, do ONE unit of work, write substrate artifacts, append one Timeline entry and one LOG line. Use for loop mode, /geo:loop, scheduled GEO runs, or continuous monitoring.
content-scoring
Score content against the 10 GEO criteria with evidence and prioritized fixes. Use when users ask to score, rate, evaluate, or estimate ranking strength.
competitive-analysis
Analyze AI-search competitors for a query and recommend ranking strategy. Use when users ask competitor analysis, who ranks, or competitive landscape.
schema-generator
Generate JSON-LD schema markup for pages and content types with an implementation checklist. Use when users ask for schema, structured data, rich snippets, or markup.