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/deliverability-qa)<a href="https://agentmods.dev/skills/aaron-he-zhu/aaron-marketing-skills/deliverability-qa"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/deliverability-qa/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/deliverability-qa"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/deliverability-qa.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 | $0.00198 | $0.03688 |
| Opus 5 | $0.00099 | $0.01844 |
| Sonnet 5 | $0.00040 | $0.00738 |
| Haiku 4.5 | $0.00020 | $0.00369 |
Grade A, and why
deliverability-qa 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 10d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deliverability QA
One-time pre-flight snapshot before a send — authentication, domain/IP reputation, inbox placement, a spam-content/link/render scan, and point-in-time list hygiene — delivered as a per-qualified-item Pass/Partial/Fail/Unknown/N/A read plus an S1 authentication evidence flag. Emit the SEND S (Sender-integrity / Deliverability) dimension score only at 100% applicable coverage; otherwise return NEEDS_INPUT/UNDECIDED/NOT_SCORED and the exact gaps. This is the pre-send snapshot, not the standing watch owned by list-hygiene-monitor. Scope guard: this skill builds and, when complete, scores SEND-S, and runs the S1 authentication pre-flight only; it does NOT compute the profile-weighted EQS or enforce the S1/S2/N1/D1 vetoes — that is email-quality-auditor.
Quick Start
Run a deliverability pre-flight for [sending domain] before I send. Here is my DMARC RUA report, a DNS export, and my seed-list inbox-placement test: [paste/path].
Check my SPF/DKIM/DMARC/BIMI and my bounce + spam-complaint rates, then give me a pre-send checklist I can run myself. ESP: [name]. Profile: [promotional / retention / cold-outbound / newsletter].
Why am I hitting the Promotions tab / spam? Here is my inbox-placement seed test and ESP deliverability report — score my SEND S and flag S1.
Skill Contract
Expected output: a deliverability pre-flight (Pass/Partial/Fail/Unknown/N/A per qualified item), an S1 authentication evidence flag (pass / partial / veto-candidate / unknown), a spam-content/link/render scan, a list-hygiene read, the typed profile, and either a complete-coverage SEND S score or NEEDS_INPUT/UNDECIDED/NOT_SCORED with exact gaps, plus the standard handoff summary.
- Reads: sending domain + SEND profile (
promotional|retention|cold-outbound|newsletter); a DNS export of SPF/DKIM/DMARC/BIMI records; the DMARC aggregate (RUA) report; a seed-list / inbox-placement test (inbox vs spam/promotions); the ESP deliverability report and sending-domain/IP reputation (Postmaster / SNDS); the campaign/creative HTML for the content/link/render scan. Consult consent-registry forS2list-consent context only — leave theS2verdict to the auditor. - Writes: a user-facing pre-flight report plus a reusable SEND-
Ssummary tomemory/email/deliverability-qa/. - Promotes: deliverability blockers (auth failing/unaligned, no DMARC record, reputation degraded, inbox-placement below threshold, bounce/complaint over benchmark) and the SEND-
Sscore tomemory/hot-cache.mdandmemory/open-loops.md; propose durable auth/domain decisions as pending-decision items — do not writedecisions.mddirectly. - Done when: every applicable
Sitem is Pass/Partial/Fail/Unknown/N/A with evidence or a gap reason (never pass-by-default); theS1evidence flag is pass, partial, veto-candidate, or unknown; the scan and hygiene read are stated; and the typed profile emits anSscore only at complete applicable coverage, otherwiseNEEDS_INPUT/UNDECIDED/NOT_SCOREDwith no score. - Primary next skill: email-quality-auditor to score the full EQS and enforce
S1/S2/N1/D1onceSis verified.
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.
- 10d ago Changed c59b5ab30763
- 13d ago First seen · 96 lines · 198 tokens per session scan A d5a2d29db8b3
deliverability-qa 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 198 tokens to every session and 3,688 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 2026-08-30.
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-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.