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 JasonColapietro/suede-creator-skills --skill suede-marketing-psychologygit clone --depth 1 https://github.com/JasonColapietro/suede-creator-skillsWrote 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/jasoncolapietro/suede-creator-skills/suede-marketing-psychology)<a href="https://agentmods.dev/skills/jasoncolapietro/suede-creator-skills/suede-marketing-psychology"><img src="https://agentmods.dev/badge/skills/jasoncolapietro/suede-creator-skills/suede-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/jasoncolapietro/suede-creator-skills/suede-marketing-psychology"><img src="https://agentmods.dev/badge/skills/jasoncolapietro/suede-creator-skills/suede-marketing-psychology.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00092 | $0.00894 |
| Opus 5 | $0.00046 | $0.00447 |
| Sonnet 5 | $0.00018 | $0.00179 |
| Haiku 4.5 | $0.00009 | $0.00089 |
Grade A, and why
suede-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 12d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Suede Ethical Marketing Psychology
Suede applies behavioral models as ethical, testable hypotheses—not as universal explanations or permission to manipulate. Identify the relevant mechanism, state its evidence limits, translate it into a specific marketing application, and define how the user can measure whether it helped.
How to Use This Skill
Read .agents/product-marketing.md first if it exists and ask only for what it does not cover; see suede-product-marketing for path fallbacks.
Then:
- Use the Quick Reference table below to narrow the user's challenge to two or three candidate models.
- Read only those entries from
references/model-catalog.md— the full library, with an evidence tier on every entry. Read it whenever you are about to name a model; never recommend one from memory, because the tier is what bounds the claim you are allowed to make. - Emit one block per recommendation using the contract below. No recommendation ships without all four parts.
Per-recommendation contract
**Mechanism:** [named model] — [the behavior it predicts, in one sentence]
**Evidence:** [Robust / Context-dependent / Contested / Folklore / Framework,
copied from the catalog entry] — [what that tier means for how hard you may
lean on it here]
**Application:** [the specific change to this product, page, price, or
sequence — not a generic tactic]
**Test:** [what changes, what you measure, the success threshold, and how long
it runs before you decide]
If the catalog entry is Contested or Folklore, say so inside the recommendation and present the application as an experiment to run, never as a reason the change will work. If nothing in the catalog fits, say that rather than stretching a model — an unevidenced behavioral claim is out of bounds no matter how plausible it sounds.
Quick Reference
When facing a marketing challenge, consider these models, then pull their entries from references/model-catalog.md:
| Challenge | Relevant Models |
|---|---|
| Low conversions | Hick's Law, Activation Energy, BJ Fogg Behavior Model |
| Price objections | Anchoring, Framing, Mental Accounting, Loss Aversion |
| Building trust | Authority, Social Proof, Reciprocity, Pratfall Effect |
| Increasing urgency | Scarcity, Loss Aversion, Zeigarnik Effect |
| Retention/churn | Endowment Effect, Switching Costs, Status-Quo Bias |
| Growth stalling | Theory of Constraints, Local vs Global Optima, Compounding |
| Decision paralysis | Paradox of Choice, Default Effect, Nudge Theory |
| Onboarding | Goal-Gradient, IKEA Effect, Commitment & Consistency |
What ships with it
4 files 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.
- 12d ago First seen · 76 lines · 92 tokens per session scan A dad5e8e99cd3
suede-marketing-psychology is a skill published in the GitHub repository JasonColapietro/suede-creator-skills (135 stars, last pushed today), licensed MIT. It adds 92 tokens to every session and 894 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 2026-08-30.
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generate-report
Generate a comprehensive summary report of the latest experiment including metrics, plots, and comparison with baseline. Use this after training and evaluation to create a shareable experiment summary.
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api-test
Run API integration tests against the running backend, verify endpoints return expected responses and status codes. Use after deploying a preview or starting the dev server.
run-simulator
Build and launch the app in the iOS Simulator. Automatically selects an appropriate simulator device, boots it if needed, and installs and launches the app.