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/message-test-designer)<a href="https://agentmods.dev/skills/aaron-he-zhu/aaron-marketing-skills/message-test-designer"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/message-test-designer/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/message-test-designer"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/message-test-designer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
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 | $0.00190 | $0.03327 |
| Opus 5 | $0.00095 | $0.01664 |
| Sonnet 5 | $0.00038 | $0.00665 |
| Haiku 4.5 | $0.00019 | $0.00333 |
Grade A, and why
message-test-designer 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 9d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Message Test Designer
Designs the pre-scale message validation for a candidate narrative — the hypothesis, the target panel and recruit criteria, the comprehension / 5-second / message-market-fit (Wynter-style) protocols, the stimulus set drawn from the canon, the success thresholds, and the stop/revise decision rule. It sits in the Evaluate phase of the TALE loop and feeds the E sub-item the message is tested before scale (comprehension / 5-second / message-market-fit panel) — see tale-benchmark.md. Its output is a test design spec only: this skill designs the test, hands execution to the experiment builders, and never runs the panel, analyzes results, or adjudicates a claim. It also encodes the E1 discipline downstream — a message that fails its test triggers revision, not louder repetition (the narrative-whiplash guardrail's counter-move).
Scope guard: this skill produces the test design document only. It does not run the panel or the A/B experiment (hand execution to send-experiment-designer or ad-test-designer), analyze the returned results (use performance-analyzer), author or edit the message under test (message-system-architect owns the durable house), adjudicate any claim in the stimulus (unverifiable claims are marked [needs source] and submitted to memory/events/claims.ndjson via an authorized operation: propose request to registry-events.py — offer-claims-registry is the sole adjudicator), or compute the TALE profile result (only the narrative-quality-auditor gate scores TALE). It works one lever — test design — and hands off.
Quick Start
Design a message-market-fit panel test for [tagline / one-liner]. Target panel: [role / segment]. Variants: [list or "single"].
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 93 lines · 190 tokens per session scan A ec7ffb03a792
message-test-designer is a skill published in the GitHub repository aaron-he-zhu/aaron-marketing-skills (2,767 stars, last pushed yesterday), licensed Apache-2.0. It adds 190 tokens to every session and 3,327 once invoked, about $0.0010 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 2026-09-03.
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.