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/memory-management)<a href="https://agentmods.dev/skills/aaron-he-zhu/aaron-marketing-skills/memory-management"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/memory-management/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/memory-management"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/memory-management.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 | $0.00077 | $0.02497 |
| Opus 5 | $0.00039 | $0.01248 |
| Sonnet 5 | $0.00015 | $0.00499 |
| Haiku 4.5 | $0.00008 | $0.00250 |
Grade A, and why
memory-management 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Management
Manages the project's authorized working memory. HOT/WARM/COLD notes improve retrieval; they are not a second truth system. The seven registry event streams remain canonical, their JSON projections are rebuildable views, and only registry owners may accept or mutate canonical facts.
Quick Start
Initialize private runtime memory from the repository templates.
Show current priorities and their source records.
Consolidate duplicate notes without changing registry truth.
Archive WARM files not updated in 90 days.
Purge subject-7f42 from project memory under this confirmed erasure request.
Skill Contract
Reads: authorized runtime memory, registry projections/events, approved decisions, and state-model.md. Writes: HOT/WARM/COLD notes, archives, indexes, and authorized tombstone/erase events; it never accepts registry proposals or writes canonical facts on behalf of an owner. Done when: the requested operation is complete, writes have explicit authorization, affected paths/events are reported, HOT is within 80 lines and 25 KB, and registry verification still passes.
Operational memory/** is Git-ignored by default. Initialize from memory/templates/; never commit runtime data, event streams, projections, audits, exports, or subject records unless the user deliberately creates a separate protected data-governance process.
Authority Order
When sources conflict, use this order:
- live consent suppression replay for send eligibility;
- accepted registry projection at a named event offset;
- user-approved decision with provenance;
- dated WARM evidence artifact;
- HOT pointer or summary;
- COLD historical note.
Lower layers cannot override higher ones. A conflict with registry truth becomes a proposal to the owner, never a direct edit.
Handoff Summary
Use skill-contract.md. Include authorization status, changed paths/event IDs, registry offsets read, conflicts preserved, privacy actions, and one next skill.
What ships with it
7 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.
- 9d ago First seen · 154 lines · 77 tokens per session scan A 1a3fdc9a02d7
memory-management 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 77 tokens to every session and 2,497 once invoked, about $0.0004 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.