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/narrative-drift-monitorWrote 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/narrative-drift-monitor)<a href="https://agentmods.dev/skills/aaron-he-zhu/aaron-marketing-skills/narrative-drift-monitor"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/narrative-drift-monitor/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/narrative-drift-monitor"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/narrative-drift-monitor.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 68 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 | $0.00216 | $0.03444 |
| Opus 5 | $0.00108 | $0.01722 |
| Sonnet 5 | $0.00043 | $0.00689 |
| Haiku 4.5 | $0.00022 | $0.00344 |
Grade A, and why
narrative-drift-monitor 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Narrative Drift Monitor
Watches a live narrative for drift after it has landed — the surfaces that have quietly drifted away from the narrative-registry canon over time, the competitors that have repositioned, the explicit conditions that should (and should not) trigger a repositioning of your own message, and a D1/W1/M1 message-shift retro of intended-vs-actual pull-through. It is the last move of the TALE Evaluate phase and feeds two TALE-L items — a message-consistency pass is run before any flagship surface ships a major change and the cross-surface matches-the-canon check over time — plus it is the recorded fact base for the narrative-whiplash guardrail under A (re-cutting the narrative faster than the market can absorb it, with no triggering evidence). It measures change history with scripts/connectors/wayback.py (Measured, each snapshot carrying an as-of date) and reads competitor narrative context from category-narrative-mapper; it never scores.
Scope guard: this skill produces the drift report and repositioning-trigger set only. It does not run the first-time consistency check before a surface ships (that is narrative-cascade-planner), compute the TALE profile result or run the TALE vetoes (only the narrative-quality-auditor gate scores), measure echo rate / share-of-voice / AI-answer resonance (that is narrative-resonance-monitor), author or re-version the canon (message-system-architect proposes, narrative-registry is the sole writer of memory/narrative-registry/), or adjudicate any claim it surfaces (unverifiable claims are marked [needs source] and submitted to memory/events/claims.ndjson via an authorized operation: propose request to registry-events.py). It works one lever — drift over time — and hands off.
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 · 89 lines · 216 tokens per session scan A 3b5dc0db62b1
narrative-drift-monitor 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 216 tokens to every session and 3,444 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.