菜单
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.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/hashgraph-online/awesome-codex-plugins --skill trust-and-liking命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
Coordinate agents via the AMQ CLI for file-based inter-agent messaging. Use this skill whenever you need to send messages to another agent (codex, claude, or any named handle), check your inbox, drain queued messages, set up co-op mode between agents, join a swarm team, route messages across projects, or diagnose delivery issues. Also use it when you receive a message and need to know how to reply, inspect receipts, or handle priority. Covers any multi-agent coordination task where agents need to talk to each other — review requests, questions, status updates, decision threads, wake notifications, and orchestrator integration (Symphony, Kanban). For collaborative spec/design workflows specifically, prefer the /amq-spec skill which provides structured phase-by-phase guidance. Not intended for distributed systems design (RabbitMQ, Kafka), CI/CD pipelines, or single-agent tasks with no partner.
Parallel-research-then-converge design workflow between two agents. Use this skill when the user wants two agents to independently think through a design problem before aligning on a solution — "spec X with codex", "design X together", "both agents think through X", "brainstorm architecture together", "parallel research then joint proposal", "think through separately then align", "careful thought from both sides before coding", or any variation where the user wants collaborative design rather than just splitting implementation work. Also use this when you receive a message labeled workflow:spec and need to know the correct receiver-side protocol. Not for sending simple messages or reviews (use /amq-cli), implementing completed designs, or creating document templates.
Use when defining new features, product behavior, UI/component design, architecture choices, contract changes, or ambiguous medium/high-complexity work before implementation, or when the user asks to grill or pressure-test a plan or design.
基于 SOC 职业分类
| 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"} |
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.
guidelines.md to choose the smallest useful reference set.references/liking/knowledge.md for concepts and references/liking/rules.md for operating rules.workflows/build-rapport-without-flattery.md for repeatable tasks.| 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. |
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.