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/trend-spotter)<a href="https://agentmods.dev/skills/aaron-he-zhu/aaron-marketing-skills/trend-spotter"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/trend-spotter/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/trend-spotter"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/trend-spotter.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 | $0.00107 | $0.02413 |
| Opus 5.5 | $0.00043 | $0.00965 |
| Sonnet 5.5 | $0.00021 | $0.00483 |
| Haiku 4.5 | $0.00011 | $0.00241 |
Grade A, and why
trend-spotter 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 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.
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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trend Spotter
This skill helps you identify and capitalize on trends that matter to your audience. It monitors social conversations, emerging topics, viral content formats, and cultural moments to inform influencer campaign timing and content strategy.
Quick Start
Shortest invocation:
What trends are relevant for [brand/industry] right now?
Common scenario — analyze one specific trend before committing:
Should [brand] participate in [trend/challenge]? Score the brand fit and give a go/skip call.
Skill Contract
- Reads: brand/industry, target platforms, audience, geographic focus, time horizon, content categories; prior audience and niche findings from
memory/influencer/if present. - Writes: return the trend report inline by default; save it to
memory/influencer/trend-spotter/YYYY-MM-DD-<topic>.mdonly with exact authorization for that WARM path. - Promotes: only with separate exact authorization, promote durable facts (top trends to act on now, trends to avoid, next review date) to
memory/hot-cache.md. - Done when:
- Every named current trend, volume/growth/status claim, cultural moment, and competitor-adoption claim has a dated source ref plus the requested platform, geography, observation window, metric definition, and momentum comparison.
- Each candidate with complete current evidence for that exact scope has a brand-fit score and a go / caution / skip call; RSS/title overlap alone remains a
Proxy candidatewithscore_state: NOT_SCORED. - The report names the top 3 trends, watch list, and avoid list only when current evidence supports them; otherwise it returns
NEEDS_INPUTwith an exact query/collection plan.
- Primary next skill: influencer-discovery — find the creators who can execute the chosen trends.
Handoff Summary
Emit the standard shape from skill-contract.md §Handoff Summary Format.
Data Sources
What ships with it
2 files 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.
- 1mo ago Changed · +2 lines 5b032ce53b01
- 1mo ago First seen · 101 lines · 107 tokens per session scan A ab75139739ca
trend-spotter 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 107 tokens to every session and 2,413 once invoked, about $0.0004 per session on Opus 5.5. 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
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.