Trust and Liking
SkillCommunicationUse 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.
Use Trust and Liking in Claude, ChatGPT or Ahel Desktop
Free. Sign in, add Trust and Liking and connect your AI. About a minute.
Also: Claude Code · Cursor · Codex
Then ask your AI: use the Trust and Liking skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by hashgraph-online/awesome-codex-plugins in plugins/LVTD-LLC/skills/skills/trust-and-liking/SKILL.md and read by Ahel’s review.
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.
Signals
- GitHub stars
- 1k
- Forks
- 316
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
trust-and-liking- Source
- github.com/hashgraph-online/awesome-codex-plugins
github.com/hashgraph-online/awesome-codex-plugins
More in Communication
Skill · anthropics
More in Communicationerror-handling
Skill · affaan-m
More in Communicationemails
Skill · coreyhaines31
More in Communicationwait-what
Skill · mattpocock
More in Communicationcold-email
Skill · coreyhaines31
More in Communicationazure-messaging
Skill · microsoft
More in Communication