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 vasilyu1983/AI-Agents-public --skill foundations-consumer-neurosciencegit clone --depth 1 https://github.com/vasilyu1983/AI-Agents-publicWrote 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/vasilyu1983/ai-agents-public/foundations-consumer-neuroscience)<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/foundations-consumer-neuroscience"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/foundations-consumer-neuroscience/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/vasilyu1983/ai-agents-public/foundations-consumer-neuroscience"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/foundations-consumer-neuroscience.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, 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 174 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.
- medium Excessive Agency · line 179 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.
- medium Excessive Agency · line 198 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.
- medium Excessive Agency · line 180 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.
- medium Excessive Agency · line 475 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.
- low Excessive Agency · line 174 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
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 | $0.00046 | $0.15062 |
| Opus 5 | $0.00023 | $0.07531 |
| Sonnet 5 | $0.00009 | $0.03012 |
| Haiku 4.5 | $0.00005 | $0.01506 |
Grade A, and why
foundations-consumer-neuroscience 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 — 484 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Consumer Neuroscience Foundations
12 canonical consumer-neuroscience primitives for product, content, interface, and retention design. Each primitive is domain-agnostic and ethically bounded. Primitives 1–8 cover engagement-time neural responses (salience, arousal, bonding, narrative, regulatory orientation, social mirroring, aesthetics, interoception). Primitives 9–12 cover temporal and predictive mechanisms (memory consolidation, reward anticipation, embodied cognition, predictive processing). Primitive #10 (reward anticipation, Berridge "wanting" vs "liking") is intentionally distinct from foundations-behavioral-economics primitive #13 (reinforcement schedules / dopamine prediction-error): that skill covers schedule-of-reinforcement design; this skill covers anticipatory dopamine as a separate design lever — countdown UX, drop reveals, daily-card open, pre-purchase excitement. Primitive #12 (predictive processing & active inference) is the unifying primitive that grounds attention (#1), interoception (#8), and narrative (#4) under one prediction-error-minimization frame: the brain continuously generates predictions; violations of priors incur a prediction-error cost that must be "earned" by the design.
Ethical obligation: every primitive in this skill operates on pre-conscious or sub-deliberative neural systems. The manipulation risk is higher than for behavioral-economics nudges, because users cannot easily introspect on the mechanism. Read the Misuse Boundary subsection in each playbook before applying any technique. The test from Thaler and Sunstein: "Would you be embarrassed if the technique appeared on the front page of a newspaper?" If yes, it is exploitation, not design. The DMCC Act 2024, in force from 6 April 2025, makes online choice architecture and dark patterns directly actionable by the CMA with fines up to 10% of global annual turnover.
When to Apply
Apply consumer-neuroscience when:
- Attention/salience design — first-7-second hook, visual hierarchy, modal vs inline
- Anxiety-driven engagement loops (cosmic, dating, status apps) — needs DMCC ethical audit
- Parasocial / narrative-led conversion (creator content, branded characters)
- Daily-cadence retention with timing-sensitive triggers (consolidation windows, wake-time)
- Trust repair, reciprocity, or oxytocin-bond design in social/community products
What ships with it
27 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.
- agents/openai.yaml 386 B
- assets/playbooks/README.md 1.5 KB
- assets/playbooks/signal-to-design-cookbook.md 14 KB
- assets/playbooks/study-design.md 12 KB
- assets/templates/consumer-neuroscience/01-attention-salience.md 5.6 KB
- assets/templates/consumer-neuroscience/02-arousal-physiology.md 6.6 KB
- assets/templates/consumer-neuroscience/03-social-bonding.md 6.7 KB
- assets/templates/consumer-neuroscience/04-narrative-transportation.md 6.6 KB
- assets/templates/consumer-neuroscience/05-approach-avoidance.md 5.8 KB
- assets/templates/consumer-neuroscience/06-mirror-systems.md 6.4 KB
- assets/templates/consumer-neuroscience/07-neuroaesthetics.md 6.5 KB
- assets/templates/consumer-neuroscience/08-interoception-somatic.md 6.5 KB
- assets/templates/consumer-neuroscience/09-memory-consolidation.md 6.1 KB
- assets/templates/consumer-neuroscience/10-reward-anticipation.md 7.2 KB
- assets/templates/consumer-neuroscience/11-embodied-cognition.md 7.3 KB
- assets/templates/consumer-neuroscience/12-predictive-processing.md 7.6 KB
- assets/templates/consumer-neuroscience/README.md 5.0 KB
- data/sources.json 43 KB
- learnings.consolidated.md 609 B
- learnings.md 654 B
- references/biomarker-signal-dictionary.md 13 KB
- references/ethics-operational-checklist.md 14 KB
- references/formal-theory-map.md 6.2 KB
- references/frameworks-meta.md 11 KB
- references/instrumentation-vendor-landscape.md 14 KB
- references/patterns-scenarios-traps.md 6.1 KB
- references/primitives-overview.md 14 KB
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 · 484 lines · 46 tokens per session scan A f565da077ada
foundations-consumer-neuroscience is a skill published in the GitHub repository vasilyu1983/AI-Agents-public (87 stars, last pushed 10d ago), licensed MIT. It adds 46 tokens to every session and 15,062 once invoked, about $0.0002 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.
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