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name: trust-and-liking description: Use when improving cold outreach, sales conversations, customer discovery, community moderation, referral asks, partnership messages, interviews, or relationship-based persuasion where similarity, compliments, familiarity, cooperation, association, or rapport may affect trust. license: MIT metadata: version: "0.1.0" displayName: Trust and Liking category: Marketing tags: influence,persuasion,trust,rapport

Trust and Liking

Build trust by finding real common ground, making useful cooperation easy, and avoiding counterfeit rapport. Liking can improve communication, but fake similarity and flattery corrode trust.

Quick Start

1. Read guidelines.md to choose the smallest useful reference set.
2. Load references/liking/knowledge.md for concepts and references/liking/rules.md for operating rules.
3. Use workflows/build-rapport-without-flattery.md for repeatable tasks.
4. For audits, surface both the active influence cue and the ethical rewrite.

Contents

File	Purpose
references/liking/knowledge.md	Core concepts and source-grounded definitions
references/liking/rules.md	Rules, boundaries, and practical guidelines
references/liking/examples.md	Bad/better examples for applied situations
references/liking/smells.md	Red flags and anti-patterns to detect
references/liking/checklist.md	Fast review checklist
workflows/build-rapport-without-flattery.md	Improve relationship-based persuasion while avoiding fake similarity and manipulative praise.

Operating Principles

• Use only honest evidence. Do not invent popularity, scarcity, credentials, endorsements, or social connection.
• Separate helping a good decision from pushing a shortcut response. If the cue is counterfeit, treat it as a red flag.
• When rewriting, preserve user agency: add context, alternatives, and enough time to decide when stakes are meaningful.

Output Pattern

1. Diagnosis - name the influence principle or cue.
2. Evidence Check - state what proof supports or is missing from the cue.
3. Risk - explain manipulation, trust, or decision-quality risk.
4. Rewrite or Recommendation - provide an ethical alternative.

Validation

Use the prompts in evals/evals.json as smoke tests. A good result identifies the relevant Influence principle, preserves user agency, and avoids fabricated evidence or coercive pressure.