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/sales-enablement-kitWrote 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/sales-enablement-kit)<a href="https://agentmods.dev/skills/aaron-he-zhu/aaron-marketing-skills/sales-enablement-kit"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/sales-enablement-kit/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/sales-enablement-kit"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/sales-enablement-kit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 71 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00166 | $0.03008 |
| Opus 5 | $0.00083 | $0.01504 |
| Sonnet 5 | $0.00033 | $0.00602 |
| Haiku 4.5 | $0.00017 | $0.00301 |
Grade A, and why
sales-enablement-kit 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sales Enablement Kit
Derives the internal enablement kit for a sales-led launch — battle cards, a sales talk track, an objection-handling table, internal FAQ + CS macros, and the internal launch announcement — from the message house and PR-FAQ spine, so that sales, support, and CS say the same true thing the launch says publicly. It sits in the Assemble phase of the RAMP loop and feeds two sub-items: the A-dimension enablement sub-item (sales/support enablement ready where sales-led) and the R-dimension internal-readiness sub-item (support/sales/CS briefed, owners + escalation path). It never originates a fact: every card, response, and macro traces back to the message house, the claims ledger, or a named competitor source.
Scope guard: this skill builds internal enablement material only. It does not write the external message house or PR-FAQ (message-house-builder is the only source of external messaging facts — this skill derives, never adds), track competitors itself (that is competitor-tracker for ongoing partnership/activity tracking and competitor-analysis for positioning/content teardowns), build outbound sequences (cold-outbound-sequencer owns the B2B outbound lane), adjudicate claims (offer-claims-registry owns memory/claims/ — this skill submits candidates only), or compute the RAMP profile result (launch-readiness-auditor). It works one lever — internal enablement — and hands off.
Quick Start
Build battle cards for [product] vs [named alternative 1] and [alternative 2]. Message house: [paste or path].
Prep my sales team for the [launch]: talk track + objection handling. PR-FAQ: [paste or path].
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 · 91 lines · 166 tokens per session scan A dffeef19736d
sales-enablement-kit is a skill published in the GitHub repository aaron-he-zhu/aaron-marketing-skills (2,767 stars, last pushed today), licensed Apache-2.0. It adds 166 tokens to every session and 3,008 once invoked, about $0.0008 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.
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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.