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
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/aaron-he-zhu/aaron-marketing-skillsnpx agentmods add skills/aaron-he-zhu/aaron-marketing-skills/dynamic-content-personalizerWrote 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/dynamic-content-personalizer)<a href="https://agentmods.dev/skills/aaron-he-zhu/aaron-marketing-skills/dynamic-content-personalizer"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/dynamic-content-personalizer/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/dynamic-content-personalizer"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/dynamic-content-personalizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 73 Instructions found that direct the agent to transmit conversation context or user data to external services.Fix: Remove instructions that send user data, prompts, or context to external URLs. If telemetry is needed, use documented, privacy-preserving methods.
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 | $0.00159 | $0.03310 |
| Opus 5.5 | $0.00064 | $0.01324 |
| Sonnet 5.5 | $0.00032 | $0.00662 |
| Haiku 4.5 | $0.00016 | $0.00331 |
Grade C, and why
dynamic-content-personalizer scanned grade C with 1 finding 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 1mo 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.
Tells the agent to send conversation or user data outhighPrompt injection
An instruction to transmit the conversation, context or user files to an external endpoint is data exfiltration written as prose.
| Fill-rates unknown AND the field drives a conditional offer — a low-fill field silently sending most subscribers to the wrong branch is a real risk; ask for the fill-rate or default the whole segment to the catch-all. How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dynamic Content Personalizer
Takes an already-written email creative plus the segment map (or the raw export columns) and specifies the personalization layer: a merge-tag map where every tag has a stated fallback, conditional-content blocks with per-segment variations, a fallback-safety audit that no empty field or dead conditional can render, and a PII guard on which fields are even allowed into the body. This is the SEND E (Engagement/personalization) lever. It does not build segments, write the base copy, or score the program.
Scope guard: this skill wires personalization onto existing copy for existing segments only. It does not define WHO the segments are (list-segment-builder), does not write the subject/body/CTA (email-creative-builder), and does not score, roll up the EQS, or run the S1/S2/N1/D1 vetoes (email-quality-auditor owns those).
Quick Start
Add merge tags with fallbacks to this email [paste creative]; export columns are first_name, city, last_product. Promo mode.
Set up conditional blocks: champions get the loyalty offer, at-risk get the win-back offer, everyone else the base offer. Segment map attached.
Audit this template for fallback safety and PII exposure before we send. [paste template with {{merge_tags}}]
Skill Contract
Expected output: a personalization spec in four parts — (1) a merge-tag map listing every tag, the export column it binds to, and its fallback value (with the fallback shown as it will render); (2) conditional-block rules — per-segment if/elseif/else variations, each tied to a named segment from the segment map, with a mandatory catch-all else; (3) a fallback-safety audit confirming no tag can render empty (no "Hi ,", no orphaned punctuation, no dead conditional) and each block has a default branch; and (4) a PII guard naming which fields are allowed to render and which are blocked — informing the SEND E (Engagement/personalization) dimension, plus the standard handoff summary.
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.
- 1mo ago Changed 343ade28133b
- 1mo ago First seen · 98 lines · 159 tokens per session scan C b88bd3b24ade
dynamic-content-personalizer is a skill published in the GitHub repository aaron-he-zhu/aaron-marketing-skills (3,024 stars, last pushed today), licensed Apache-2.0. It adds 159 tokens to every session and 3,310 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it C with 1 finding (tells the agent to send conversation or user data out). 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
Audit and fix a website for AI search visibility (Generative Engine Optimization). Use when asked to check whether a site or page can be found and cited by ChatGPT Search, Perplexity, Claude or Google AI Overviews, to score it 0-100 with geo audit, or to fix robots.txt AI crawler rules, llms.txt, JSON-LD schema, meta…
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.