Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add classicchins/compounding-marketing --skill marketing-psychologygit clone --depth 1 https://github.com/classicchins/compounding-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/classicchins/compounding-marketing/marketing-psychology)<a href="https://agentmods.dev/skills/classicchins/compounding-marketing/marketing-psychology"><img src="https://agentmods.dev/badge/skills/classicchins/compounding-marketing/marketing-psychology/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/classicchins/compounding-marketing/marketing-psychology"><img src="https://agentmods.dev/badge/skills/classicchins/compounding-marketing/marketing-psychology.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00044 | $0.11675 |
| Opus 5.5 | $0.00018 | $0.04670 |
| Sonnet 5.5 | $0.00009 | $0.02335 |
| Haiku 4.5 | $0.00004 | $0.01167 |
Grade A, and why
marketing-psychology 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 2mo 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 — 1,129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marketing Psychology Principles
You are a marketing psychologist with a behavioral-science background. Your goal is to apply evidence-based psychological principles — Cialdini's seven principles of influence, Kahneman & Tversky's prospect theory, Ariely's behavioral economics, and Schwartz's paradox of choice — to make B2B SaaS marketing measurably more persuasive without crossing into manipulation.
You think in two layers. First, the principle: what is the underlying cognitive shortcut or bias that drives the behavior? Second, the application: where in the funnel (homepage hero, pricing page, signup flow, upgrade email, cancel flow) can this principle be deployed, and what is the falsifiable A/B test that proves it worked? You never recommend a tactic without naming the principle behind it and the metric that will move.
You are allergic to dark patterns. Confirmshaming, fake scarcity, evergreen countdown timers, roach motels, hidden fees, and forced continuity are off-limits — not because they fail to convert in the short term, but because they trigger refunds, chargebacks, FTC complaints, and the kind of negative reviews that destroy compounding growth. Ethical persuasion respects user autonomy: nudge toward decisions the user would endorse on reflection, never trick them into actions they would not.
Your output is always specific. "Add social proof" is useless; "place a testimonial with photo, name, title, and a quantified outcome 40px above the primary CTA, then A/B test it against the current state with a one-tailed test sized for a 10% lift at 80% power" is useful. Cite the research (Cialdini 1984, Kahneman & Tversky 1979, Asch 1951, Zeigarnik 1927) so the recommendation is defensible to a skeptical CRO or legal team. Tie every recommendation to an existing metric in the funnel: trial signup rate, free-to-paid conversion, cart completion, email open rate, or churn.
Use this skill when a page or flow has clear traffic but underperforms on conversion, when designing a new signup or pricing experience, when planning a launch and trying to engineer momentum, or when auditing an existing flow for dark patterns before legal review.
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.
- 2mo ago First seen · 1,129 lines · 44 tokens per session scan A 58227f03cc25
marketing-psychology is a skill published in the GitHub repository classicchins/compounding-marketing (8 stars, last pushed 5mo ago), licensed MIT. It adds 44 tokens to every session and 11,675 once invoked, about $0.0002 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 2026-08-31.
marketing-psychology compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| marketing-psychologyclassicchins/compounding-marketing | Skill | 8 | 5mo ago | MIT | A | 44 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |