One paragraph describing what this agent does, who it's for, and when to activate it.
aeo
aeo is an open-source integrations skill for Claude Code and compatible agents, published by alirezarezvani. Its author describes it as: “Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LL…”. The project has 25k stars on GitHub and is available under the MIT license. Add it to your setup with `/plugin marketplace add alirezarezvani/claude-skills`.
What aeo does
**Get your content cited by ChatGPT, Perplexity, Claude, Gemini, and Mistral as the authoritative source.**
Installation
Add aeo to your agent with:
/plugin marketplace add alirezarezvani/claude-skillsAlways review a skill's source before installing it. This command comes from the skill's public repository; the linked repo is the source of truth for exact setup steps.
What's inside
The SKILL.md for aeo is organised into these sections:
- Distinct From SEO
- When To Use
- When NOT To Use
- Core Capabilities
- 1. Content audit + E-E-A-T scoring
- 2. Content optimization
- 3. Citation tracking
- References
- Workflow
- Configuration
- Output Format
- Markdown audit report (default)
When to use it
Reach for aeo when you want integrations help from your agent without writing the same instructions every session. Load the skill and the agent picks it up automatically for relevant tasks.
Strengths
- Clear MIT license — safe to read and adapt
- Ships in alirezarezvani/claude-skills, an established project with 24,617 GitHub stars
- Actively maintained (recent commits)
Topics
Frequently asked questions
- What does aeo do?
- Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.
- How do I install aeo?
- Run /plugin marketplace add alirezarezvani/claude-skills in your agent, then reload your skills. Review the source at https://github.com/alirezarezvani/claude-skills before installing.
- Is aeo free to use?
- Yes. aeo is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
- Where does aeo come from?
- aeo ships inside alirezarezvani/claude-skills, a repository that contains 41 catalogued skills in total. The repository's 24,617 GitHub stars apply to that whole collection, not to this skill on its own.
Related skills
More Integrations →Adversarial code review that breaks the self-review monoculture. Use when you want a genuinely critical review of recent changes, before merging a PR, or when you suspect Claude is being too agreeable about code quality. Forces perspective shifts through hostile reviewer personas that catch blind spots the author's mental model shares with the reviewer.
Mint a tamper-evident, post-quantum-signed receipt for a consequential agent action (deploy, delete, pay, grant-access, model decision) so it can be verified later from the certificate alone. Use when an autonomous agent takes a side-effecting action that may need to be proven later, or when satisfying EU AI Act Article 12 record-keeping. Three decisions: whether an action needs a receipt, minting it, verifying it. Signing is delegated to the open-source OpenAgentOntology package. Not after-the-fact log analysis; not a hosted notary; not a legal opinion.
Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.
Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.