MindFluence: An AI prompt-skill that turns 20 cognitive biases into high-converting marketing copy

by MADEVAL · Codex Skill · ★ 59

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 62/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-promptsbehavioral-economicsclaude-codecodexcognitive-biasescontent-strategyconversion-optimizationcopywritingcopywriting-aicopywriting-tool

Quick Facts

Stars59
Forks10
CategoryCodex Skill
LicenseMIT
Quality Score62/100
Last Updated2026-10-29
Created2026-06-18
Platformsbrowser, claude-code, codex
Est. Tokens~18k

About MindFluence

MindFluence English | [Русский ] Persuasion engineered through psychology, not manipulation. An AI prompt-skill that turns 20 cognitive biases into high-converting marketing copy - for any language, any platform, any audience. What is this? MindFluence is a system prompt (skill) for LLMs - GPT, Claude, Gemini, DeepSeek or any capable model.

Compatible Skills

These tools work well together with MindFluence for enhanced workflows:

  • ai-marketing-claude — semantic(0.29)+complementary+rare_topics+similar_pop+shared_platform (54%)
  • email-marketing-bible — semantic(0.26)+complementary+rare_topics+similar_pop+shared_platform (54%)
  • social-media-skills — semantic(0.24)+complementary+rare_topics+similar_pop+shared_platform (53%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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