behavioral-levers
Apply anchoring, loss aversion, social proof and framing to a specific page, price or offer.
Skill by poorvith-mp
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/poorvith-mp-behavioral-levers
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About
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/behavioral-levers
What's inside
- Skill name
behavioral-levers- Description
- Apply anchoring, loss aversion, social proof and framing to a specific page, price or offer. Use when applying loss aversion, social proof, anchoring, or nudges.
- License
- MIT
- Instructions
- 56 lines in SKILL.md · view on GitHub
Files (3)
- SKILL.md
- behavioral-levers.skill
- routing.yaml · evals/
SKILL.md (first lines)
# Behavioral Levers
Behavioral levers apply behavioral economics and cognitive heuristics to product interfaces, pricing displays, and checkout funnels. Ethical behavioral design eliminates cognitive load, anchors value expectations, frames trade-offs transparently, and leverages social proof to overcome decision paralysis.
## 1. Core Behavioral Economic Frameworks
### A. Price Anchoring & Asymmetric Decoys (Tversky & Kahneman)
- **High-Anchor First**: Present the premium enterprise tier first ($299/mo). Subsequent options ($79/mo) are cognitively perceived as affordable by comparison.
- **The Decoy Effect (Asymmetric Dominance)**:
- *Option A (Digital Only)*: $50
- *Option B (Print Only - Decoy)*: $100
- *Option C (Digital + Print Bundle)*: $100
- Option B exists solely to make Option C an irresistible value proposition.
### B. Loss Aversion & Endowment Effect
Humans feel the pain of losing something roughly **2x to 2.5x more intensely** than the pleasure of gaining the equivalent value:
- **Trial Design**: Instead of "Upgrade to get Feature X", frame as "Don't lose your custom dashboard and saved data when your trial ends on Friday."
- **Endowed Progress**: Progress bars that start pre-filled (e.g. "Step 1 of 5 already completed!") have significantly higher completion rates than empty trackers.
### C. Social Proof & Herd Behavior
Social proof must be hyper-specific to the prospect's cohort:
- *Weak*: "Trusted by thousands of developers."
- *Strong*: "Over 14,000 backend engineers use Skillary to manage agent workflows."
- Position logos, customer quotes, and verifiable metrics immediately adjacent to high-friction action points (e.g. checkout forms, credit card inputs).
### D. Choice Architecture & Default Bias
Users overwhelmingly choose the default pre-selected option:
- Set the recommended tier ("Pro / Team") as the highlighted default.
- Default billing toggles to "Annual (Save 20%)" while clearly stating the monthly equivalent price.
## 2. Decision Friction Audit Checklist
| Friction Point | Behavioral Cause | Design Solution |
|---|---|---|
| **Form Abandonment** | Analysis paralysis from too many form fields | Progressive disclosure: split into 2 low-friction micro-steps |
| **Pricing Hesitation** | Uncertainty about future costs or hidden fees | Clear risk reversal: "Cancel anytime with 1 click; 30-day full refund guarantee" |
| **Feature Overwhelm** | Paradox of Choice (Barry Schwartz) | Highlight top 3 differentiating features; collapse exhaustive feature lists |
## Critical Rules
1. Never employ deceptive "dark patterns" (hidden subscriptions, disguised ads, difficult cancellation paths); dark patterns destroy brand equity and trigger regulatory action.
2. Social proof claims and statistics must be 100% verified and factually true.
3. Every urgency trigger (e.g. "Offer ends at midnight") must represent an actual operational deadline.
## Verification Checklist
- [ ] Value anchor established before presenting secondary options.
- [ ] Social proof placed directly next to primary conversion forms and buttons.
- [ ] Endowed progress applied to multi-step signup and onboarding workflows.
- [ ] Risk reversals (money-back guarantee, no card required) explicitly stated at decision points.
- [ ] Interfaces audited to confirm zero deceptive dark patterns.
## Anti-Patterns
- NEVER use fake countdown timers that reset upon page refresh.
- NEVER pre-check optional paid add-ons or marketing spam checkboxes by default.
- NEVER hide cancellation or refund options behind phone calls or difficult support ticket queues.From poorvith-mp/skills-marketing, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Sep 12, 2026 (1 month ago)
- Last release
- Oct 2, 2026 (26 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/poorvith-mp/skills-marketing
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
behavioral-levers skill. Agent Mart. https://agentmart.dev/skills/poorvith-mp-behavioral-levers (last updated 2026-10-24)