Cold Outbound Optimizer
ericosiu/ai-marketing-skills
Design, analyze, and optimize cold outbound email campaigns for Instantly.
A skill your agent uses when improving cold outreach, sales conversations, customer discovery, community moderation, referral asks, partnership messages, interviews, or relationship-based persuasion…
Install Trust And Liking
$ npx skills add hashgraph-online/awesome-codex-plugins --skill trust-and-liking -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins trust-and-liking --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/trust-and-liking .claude/skills/trust-and-liking && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "trust-and-liking" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/trust-and-liking into .claude/skills/trust-and-liking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trust-and-liking", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/trust-and-likingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill trust-and-liking -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins trust-and-liking --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/trust-and-liking .agents/skills/trust-and-liking && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "trust-and-liking" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/trust-and-liking into .agents/skills/trust-and-liking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trust-and-liking", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill trust-and-liking -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins trust-and-liking --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/trust-and-liking .cursor/skills/trust-and-liking && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "trust-and-liking" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/trust-and-liking into .cursor/skills/trust-and-liking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trust-and-liking", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/hashgraph-online/awesome-codex-plugins.git --path plugins/LVTD-LLC/skills/skills/trust-and-liking--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill trust-and-liking -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins trust-and-liking --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/trust-and-liking .gemini/skills/trust-and-liking && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "trust-and-liking" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/trust-and-liking into .gemini/skills/trust-and-liking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trust-and-liking", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install hashgraph-online/awesome-codex-plugins trust-and-likingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add hashgraph-online/awesome-codex-plugins --skill trust-and-liking -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/trust-and-liking .github/skills/trust-and-liking && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "trust-and-liking" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/trust-and-liking into .github/skills/trust-and-liking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trust-and-liking", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill trust-and-liking -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins trust-and-liking --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/trust-and-liking .opencode/skills/trust-and-liking && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "trust-and-liking" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/trust-and-liking into .opencode/skills/trust-and-liking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trust-and-liking", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
trust-and-liking- GitHub stars
- 1.3k
- Token cost
- ~614 tokens
- SKILL.md length
- 233 words
- Files
- 10 (incl. references)
- Skills in repo
- 716
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when improving cold outreach, sales conversations, customer discovery, community moderation, referral asks, partnership messages, interviews, or relationship-based persuasion…
- Works in 4 steps: Read guidelines.md to choose the… → Load references/liking/knowledge.md for… → Use… → …
- Improving cold outreach
- SKILL.md covers Quick Start, Contents, Operating Principles and Output Pattern, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Trust And Liking is an agent skill from hashgraph-online/awesome-codex-plugins. 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.
Its SKILL.md is about 610 tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including reference files (for example `agents/openai.yaml`, `evals/evals.json` and `guidelines.md`).
It sits in Sales & Support, covering Cold outreach. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is MIT.
When your agent uses it
- Improving cold outreach
- Sales conversations
- Customer discovery
- Community moderation
Example prompts
- “/trust-and-liking”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Read guidelines.md to choose the smallest useful reference set.
- Load references/liking/knowledge.md for concepts and references/liking/rules.md for operating rules.
- Use workflows/build-rapport-without-flattery.md for repeatable tasks.
- For audits, surface both the active influence cue and the ethical rewrite.
What it can do on your machine
Read from SKILL.md and the folder at commit 3e1456a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Trust And Liking loads about 614 tokens when it runs, and up to ~2.7k if it reads all its reference files. Until then it costs about 74 tokens; SKILL.md has 233 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from hashgraph-online/awesome-codex-plugins at commit 3e1456a, republished under its MIT licence (© hashgraph-online). 233 words, ~614 tokens.
Download SKILL.mdSave it as
.claude/skills/trust-and-liking/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.- 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
- metadata.displayName
- Trust and Liking
- metadata.category
- Marketing
- metadata.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
- 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.
© hashgraph-online, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 9 other files (references) in plugins/LVTD-LLC/skills/skills/trust-and-liking of hashgraph-online/awesome-codex-plugins.
- SKILL.md
- agents/openai.yaml
- evals/evals.json
- guidelines.md
- references/liking/checklist.md
- references/liking/examples.md
- references/liking/knowledge.md
- references/liking/rules.md
- references/liking/smells.md
- workflows/build-rapport-without-flattery.md
Open the folder on GitHubat commit 3e1456a
Compare with similar skills
Trust And Liking next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Trust And Liking this skillhashgraph-online/awesome-codex-plugins | 1.3k | — | ~614 | Automated safety check: Pass | MIT | |
| Cold Outbound Optimizerericosiu/ai-marketing-skills | 3.6k | 1 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Prospectingcoreyhaines31/marketingskills | 54k | — | ~5k | Automated safety check: Pass | MIT | |
| Sales OsromangojiberryAI/gojiberryai-sales-os | 139 | — | ~2k | Automated safety check: Pass | MIT | |
| ProspectingCesarjoquin/Marketing-Skills | 202 | 1 repos | ~3.8k | Automated safety check: Pass | MIT | |
| Cold Outreach Personalizeraiskilloftheweek/claude-ai-skill-of-the-week | 149 | — | ~2.6k | Automated safety check: Pass | None |
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Questions about Trust And Liking
What does Trust And Liking do?
A skill your agent uses when improving cold outreach, sales conversations, customer discovery, community moderation, referral asks, partnership messages, interviews, or relationship-based persuasion…. Trust And Liking is an agent skill from hashgraph-online/awesome-codex-plugins. 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.
When should I use Trust And Liking?
Trust And Liking fits situations like: improving cold outreach; sales conversations; customer discovery; community moderation.
How do I install Trust And Liking in Claude Code?
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill trust-and-liking -a claude-code`. Or copy the skill folder (plugins/LVTD-LLC/skills/skills/trust-and-liking in hashgraph-online/awesome-codex-plugins) into .claude/skills/trust-and-liking in your project. Claude Code loads it when a task matches its description.
How do I install Trust And Liking in Codex?
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill trust-and-liking -a codex`. Or copy the skill folder (plugins/LVTD-LLC/skills/skills/trust-and-liking in hashgraph-online/awesome-codex-plugins) into .agents/skills/trust-and-liking in your project. Codex loads it when a task matches its description.
Can I use Trust And Liking in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill trust-and-liking -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/trust-and-liking, .gemini/skills/trust-and-liking, .github/skills/trust-and-liking and .opencode/skills/trust-and-liking in your project.
What does Trust And Liking need to run?
SKILL.md names no scripts, command-line tools or credentials: Trust And Liking is instructions for the agent only.
Does Trust And Liking access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Trust And Liking safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Trust And Liking use?
Trust And Liking is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Trust And Liking use?
About 614 tokens (SKILL.md is roughly 2.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.1k tokens, read only when the agent opens those files.
What are the alternatives to Trust And Liking?
Skills that share tags, products or a category with Trust And Liking: Cold Outbound Optimizer (ericosiu/ai-marketing-skills, 3.6k stars), Prospecting (coreyhaines31/marketingskills, 54k stars), Sales Os (romangojiberryAI/gojiberryai-sales-os, 139 stars) and Prospecting (Cesarjoquin/Marketing-Skills, 202 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Trust And Liking?
hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,267 GitHub stars. The repository holds 716 skills in this directory. The repository was last updated on October 10, 2026.
Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.