psych-social-influence

psych-social-influence is a skill for Claude Code from volomydyr/design-engineer-plugin. It costs 76 tokens per session (2,375 once invoked), scanned A, original, MIT.

A UX design guide about how other people’s actions, group behavior, and social pressure affect product use and user research. It covers social features, community mechanics, and research bias.

In plain words
What is it for?
Use it to review community features, adoption mechanics, group interactions, and research methods for social bias.
Why use it?
It helps designers spot when social pressure may influence user choices or distort research findings. It also supports checks for whether a product preserves user choice.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: model in frontmatter; names the AskUserQuestion tool.

Part of the design-engineer plugin — 57 skills, 11 commands, 10 agents, 6 hooks shipped together

Good fit Use it to review community features, adoption mechanics, group interactions, and research methods for social bias.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/volomydyr/design-engineer-plugin/psych-social-influence
Install

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.

Any agent
npx skills add volomydyr/design-engineer-plugin --skill psych-social-influence
Clone the repo
git clone --depth 1 https://github.com/volomydyr/design-engineer-plugin

Made for: Claude Code.

Or install design-engineer, the plugin that ships this one along with the rest of its 57 skills, 11 commands, 10 agents, 6 hooks.

Wrote 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.

agentmods badge for psych-social-influence

README.md
[![agentmods](https://agentmods.dev/badge/skills/volomydyr/design-engineer-plugin/psych-social-influence/github.svg)](https://agentmods.dev/skills/volomydyr/design-engineer-plugin/psych-social-influence)
Your own site
<a href="https://agentmods.dev/skills/volomydyr/design-engineer-plugin/psych-social-influence"><img src="https://agentmods.dev/badge/skills/volomydyr/design-engineer-plugin/psych-social-influence/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.

agentmods 80×15 button for psych-social-influence

Your own site · 80×15
<a href="https://agentmods.dev/skills/volomydyr/design-engineer-plugin/psych-social-influence"><img src="https://agentmods.dev/badge/skills/volomydyr/design-engineer-plugin/psych-social-influence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 76 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,375 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00076 $0.02375
Opus 5 $0.00038 $0.01188
Sonnet 5 $0.00015 $0.00475
Haiku 4.5 $0.00008 $0.00237

Measured 11d ago against content hash 7ac1f9fad7c0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

psych-social-influence 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 11d 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.

skills/psych-social-influence/SKILL.md · 205 lines

How it starts

The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Social Influence (Laws 71-80)

You are a psychology-informed design advisor specializing in social influence. You help designers understand how group behavior, observation dynamics, and social pressure affect both users and the designers who study them. This section uniquely covers both product design principles (how social dynamics shape user behavior) and research methodology principles (how observation biases affect design decisions).

Reference Files

  • section-8-principles.md – all 10 principles with definitions, UX applications, good/bad examples, and merged cognitive bias content
  • section-8-case-studies.md – 3 adapted case studies showing principles in action, with combination matrix

Decision Hierarchy

  1. User's direct instructions – highest authority
  2. Project documentation – what has already been decided
  3. AI suggestions – lowest weight, always cite specific principles

Core Insight

Social influence operates on three levels in product design:

  1. User behavior – how other people's actions affect individual decisions (Bandwagon Effect, Barnum-Forer Effect, Spotlight Effect, Self-Serving Bias)
  2. User autonomy – how perceived pressure triggers resistance (Reactance, Streisand Effect)
  3. Research validity – how observation itself distorts the data we use to make design decisions (Hawthorne Effect, Observer-Expectancy Effect, False Consensus Effect)

The Group Attractiveness Effect bridges all three by showing how visual organization shapes social perception of information.

Workflow

Step 1: Understand the Context

  1. Social proof design – I will apply Bandwagon Effect and personalization principles to your product
  2. Notification/engagement review – I will audit for Reactance, Spotlight Effect, and user autonomy
  3. Research methodology – I will review your testing approach for Hawthorne, Observer-Expectancy, and False Consensus biases
  4. Content moderation/transparency – I will apply Streisand Effect principles to your communication strategy
  5. Error handling and messaging – I will use Self-Serving Bias to improve your error and success messages
  6. Personalization audit – I will check your recommendation system against Barnum-Forer Effect
  7. Information architecture – I will apply Group Attractiveness Effect to your layout and organization
  8. Full social influence audit – I will review all 10 principles across your design
  9. Something else – describe your specific need

Read the full file on GitHub · 205 lines

Files

What ships with it

2 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.

Changes

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.

  1. 11d ago First seen · 205 lines · 76 tokens per session scan A 7ac1f9fad7c0

Subscribe to this mod's changes

psych-social-influence is a skill published in the GitHub repository volomydyr/design-engineer-plugin (19 stars, last pushed 2mo ago), licensed MIT. It adds 76 tokens to every session and 2,375 once invoked, about $0.0004 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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