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/consent-registry)<a href="https://agentmods.dev/skills/aaron-he-zhu/aaron-marketing-skills/consent-registry"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/consent-registry/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/consent-registry"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/consent-registry.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 | $0.00096 | $0.01774 |
| Opus 5 | $0.00048 | $0.00887 |
| Sonnet 5 | $0.00019 | $0.00355 |
| Haiku 4.5 | $0.00010 | $0.00177 |
Grade A, and why
consent-registry 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Consent Registry
The canonical consent and live-suppression authority. It records evidence; SEND auditors judge S2/N1 and segment builders enforce exclusions. A withdrawal must never wait as a pending proposal.
Quick Start
Record opt-in for subject sha256-7d9f with basis/proof references and timestamp.
Immediately suppress sha256-7d9f from unsubscribe webhook evt-882.
Is sha256-7d9f suppressed right now?
Skill Contract
Unit: one pseudonymous subject ID supplied by the user's system. Reads: memory/events/consent.ndjson by replay, its projection, and minimum proof references. Writes: consent events only through registry-events.py; human records are projections. Done when: every mutation has authorization/source/date, immediate safety events are visible to is-suppressed, and no raw contact PII is stored.
Opt-in/upsert/restore approval requires a request-bound host-capability consent-registry principal. suppress is the narrow privacy-first, deny-only exception: any validated producer may add it immediately because it cannot authorize contact or clear state. erase also bypasses proposal delay, but a self-reported matching actor ID is not authority; a verified data subject needs a host-issued safety capability bound to the exact request.
Handoff Summary
Use the shared handoff. Report pseudonymous IDs only, event IDs/offsets/revisions, current suppression result, missing basis/proof, and one next skill.
Data Sources
- Form/checkout/event capture reference and opt-in timestamp.
- Lawful-basis and double-opt-in proof reference.
- ESP unsubscribe, hard-bounce, and complaint event IDs.
- Fresh re-subscription proof for restore.
- Data-subject erasure request reference.
Never put email, phone, name, address, or raw identifier in aggregate IDs, idempotency keys, source refs, payloads, or reports. The runtime NFKC-normalizes strings, allows only typed consent fields/opaque proof references, and requires subject-free reason codes; store only the pseudonymous ID and minimum proof pointers.
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 · 87 lines · 96 tokens per session scan A b824f95dd1eb
consent-registry 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 96 tokens to every session and 1,774 once invoked, about $0.0005 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.
accessibility-audit
Run an accessibility audit for a SEOJuice-tracked website. Shows WCAG issues, severity distribution, and auto-fixable items. Use when the user asks about accessibility, WCAG compliance, a11y, or screen reader support.
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.