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/social-selling-plannerWrote 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/social-selling-planner)<a href="https://agentmods.dev/skills/aaron-he-zhu/aaron-marketing-skills/social-selling-planner"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/social-selling-planner/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/social-selling-planner"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/social-selling-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector 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 | $0.00219 | $0.03014 |
| Opus 5 | $0.00110 | $0.01507 |
| Sonnet 5 | $0.00044 | $0.00603 |
| Haiku 4.5 | $0.00022 | $0.00301 |
Grade A, and why
social-selling-planner 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Selling Planner
The founder/seller daily operating block for the founder-led lane: repeatable engagement, warm-touch-before-ask cadence, and trigger-response plays. It supplies Hosting and Observability evidence for program-maturity-founder; every pipeline rate still requires a declared denominator. Only social-quality-auditor scores that profile.
Scope guard: this skill produces specs and plays a human executes — ready-to-paste packages only. It automates nothing: zero mass-DM, zero connection-request automation, zero engagement automation — the LinkedIn User Agreement §8.2 red line and ECHO H1 (manufactured engagement) territory on every platform; 中文平台（微信公众号/视频号/小红书/抖音）同为硬红线（风控/封号）. The 1:1 pitch, DM, and follow-up-thread mechanics stay with outreach-manager; cold email sequences with cold-outbound-sequencer; the listening watchlist itself with social-pulse-monitor; the ECHO profile result and vetoes with social-quality-auditor. Cadence commitments are registry-grade facts — they go to memory/events/channels.ndjson via an authorized operation: propose request to registry-events.py only (channel-registry is the sole writer of memory/channels/).
Quick Start
Build my daily social-selling block: 45 minutes, target accounts [list], platform LinkedIn (user exports only).
The watchlist fired: [account] raised a Series B. Give me the trigger-response play — first move, warm touches, and when a 1:1 ask is earned.
Run the quarterly diagnostic: here is my engagement-block log, reply/meeting counts from my export, and an SSI screenshot.
Skill Contract
Expected output: the operating block — a time-boxed daily engagement-block spec with target-account tiers and a comment quality bar, warm-touch-before-ask cadence rules with an explicit ask threshold, trigger-response plays keyed to the watchlist signal types, and a quarterly diagnostic template — 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.
- 9d ago First seen · 90 lines · 219 tokens per session scan A 8da9af0bc238
social-selling-planner 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 219 tokens to every session and 3,014 once invoked, about $0.0011 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.