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/voice-dossier-builderWrote 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/voice-dossier-builder)<a href="https://agentmods.dev/skills/aaron-he-zhu/aaron-marketing-skills/voice-dossier-builder"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/voice-dossier-builder/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/voice-dossier-builder"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/voice-dossier-builder.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 70 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 | $0.00200 | $0.02890 |
| Opus 5.5 | $0.00080 | $0.01156 |
| Sonnet 5.5 | $0.00040 | $0.00578 |
| Haiku 4.5 | $0.00020 | $0.00289 |
Grade A, and why
voice-dossier-builder 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 1mo 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.
Voice Dossier Builder
Codifies how the brand AND the founder/exec actually sound — extracted from the user's own posts, emails, and decks, never invented and never borrowed from competitors — into the versioned voice record that channel-registry stores as voice-dossier.md and every Craft-phase skill (starting with social-creative-builder) reads first. It feeds two ECHO C sub-items directly — voice-card adherence (C6: per-platform register, banned phrases respected, few-shots from own posts only) and pillar-allocation adherence (C7) — and writes the per-context disclosure lines the ECHO C2 disclosure veto is later judged against (see echo-benchmark.md); social-quality-auditor does that judging, not this skill.
Scope guard: extraction, roughly 80/20 — most of the dossier comes from real own material; the interview only confirms traits and fills gaps, and nothing is invented wholesale. This skill does NOT research audiences or personas (reuse audience-mapper), maintain the dated platform norm cards (platform-norm-profiler), write posts (social-creative-builder), or score C6/C7 — and it never writes memory/channels/ directly: the finished record is submitted via memory/events/channels.ndjson via an authorized operation: propose request to registry-events.py, and channel-registry, the sole writer, promotes it. Competitor content never enters the corpus or the few-shot bank.
Quick Start
Build the voice dossier for [brand]. Here are our last 30 LinkedIn posts and 10 founder tweets: [paste/export].
Codify my founder voice from these emails and this pitch deck — I post as "I", the company account posts as "we".
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.
- 1mo ago First seen · 90 lines · 200 tokens per session scan A e58f840fb126
voice-dossier-builder is a skill published in the GitHub repository aaron-he-zhu/aaron-marketing-skills (3,024 stars, last pushed today), licensed Apache-2.0. It adds 200 tokens to every session and 2,890 once invoked, about $0.0008 per session on Opus 5.5. 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
Audit and fix a website for AI search visibility (Generative Engine Optimization). Use when asked to check whether a site or page can be found and cited by ChatGPT Search, Perplexity, Claude or Google AI Overviews, to score it 0-100 with geo audit, or to fix robots.txt AI crawler rules, llms.txt, JSON-LD schema, meta…
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.