About trust-and-liking
trust-and-liking is a marketing skill for building trust and improving communication. It focuses on genuine common ground and useful cooperation, with guidance for spotting counterfeit rapport and rewriting persuasion ethically.
Key features
- 01Identify influence cues and risks
- 02Build common ground from real evidence
- 03Avoid fake similarity and flattery
- 04Provide structured ethical rewrites
Use cases
- 01Audit flattery in marketing copy
- 02Build genuine rapport in communication
- 03Rewrite manipulative persuasive content
Install
Copy the command and run it in a terminal.
npx skills add https:/After installing, type/trust-and-likingin Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
guidelines.mdagents/openai.yamlevals/evals.jsonreferences/liking/checklist.mdexamples.mdknowledge.mdrules.mdsmells.mdworkflows/build-rapport-without-flattery.mdDetails
From the project READMETrust 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
- Read
guidelines.mdto choose the smallest useful reference set. - Load
references/liking/knowledge.mdfor concepts andreferences/liking/rules.mdfor operating rules. - Use
workflows/build-rapport-without-flattery.mdfor repeatable tasks. - 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
- Diagnosis - name the influence principle or cue.
- Evidence Check - state what proof supports or is missing from the cue.
- Risk - explain manipulation, trust, or decision-quality risk.
- 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.