Blog Strategy
AgriciDaniel/claude-blog
Blog strategy development including topic cluster architecture with hub-and-spoke design, audience mapping, competitive landscape analysis, AI citation surface strategy across ChatGPT/Perplexity/AI…
A skill your agent uses to get a brand and its content CITED and RECOMMENDED by AI answer engines — the GEO (Generative Engine Optimization) / AI-search-visibility skill.
Install AI Search Optimization
$ npx skills add social-media-skills/skills --skill ai-search-optimization -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install social-media-skills/skills ai-search-optimization --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/social-media-skills/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-search-optimization .claude/skills/ai-search-optimization && 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 "ai-search-optimization" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/ai-search-optimization into .claude/skills/ai-search-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-search-optimization", 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/social-media-skills/skills/tree/main/skills/ai-search-optimizationType 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 social-media-skills/skills --skill ai-search-optimization -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install social-media-skills/skills ai-search-optimization --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai-search-optimization .agents/skills/ai-search-optimization && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-search-optimization" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/ai-search-optimization into .agents/skills/ai-search-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-search-optimization", 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 social-media-skills/skills --skill ai-search-optimization -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install social-media-skills/skills ai-search-optimization --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai-search-optimization .cursor/skills/ai-search-optimization && 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 "ai-search-optimization" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/ai-search-optimization into .cursor/skills/ai-search-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-search-optimization", 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/social-media-skills/skills.git --path skills/ai-search-optimization--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 social-media-skills/skills --skill ai-search-optimization -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install social-media-skills/skills ai-search-optimization --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai-search-optimization .gemini/skills/ai-search-optimization && 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 "ai-search-optimization" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/ai-search-optimization into .gemini/skills/ai-search-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-search-optimization", 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 social-media-skills/skills ai-search-optimizationInstalls 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 social-media-skills/skills --skill ai-search-optimization -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai-search-optimization .github/skills/ai-search-optimization && 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 "ai-search-optimization" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/ai-search-optimization into .github/skills/ai-search-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-search-optimization", 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 social-media-skills/skills --skill ai-search-optimization -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install social-media-skills/skills ai-search-optimization --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai-search-optimization .opencode/skills/ai-search-optimization && 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 "ai-search-optimization" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/ai-search-optimization into .opencode/skills/ai-search-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-search-optimization", 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
ai-search-optimization- GitHub stars
- 134
- Token cost
- ~2k tokens
- SKILL.md length
- 837 words
- Files
- 6 (incl. references)
- Skills in repo
- 106
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses to get a brand and its content CITED and RECOMMENDED by AI answer engines — the GEO (Generative Engine Optimization) / AI-search-visibility skill.
- Works in 7 steps: Read the foundation + the goal → Run the prompt-audit (always start here) → Be retrievable (the foundation) → …
- Get cited by ChatGPT/Perplexity/Google AI
- SKILL.md covers Step 0 — Read the foundation +…, Step 1 — Run the prompt-audit…, Step 2 — Be retrievable (the… and Step 3 — Earn brand mentions…, plus 8 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
AI Search Optimization is an agent skill from social-media-skills/skills. Use to get a brand and its content CITED and RECOMMENDED by AI answer engines — the GEO (Generative Engine Optimization) / AI-search-visibility skill. Run when the user says "GEO," "get cited by ChatGPT/Perplexity/Google AI," "ChatGPT SEO," "LLM SEO / LLMO," "AI Overviews," "answer engine optimization (AEO)," "will AI recommend my brand," or wants to show up in AI-generated answers, not just the feed or Google links. Reads brand-profile and audience first. AI engines retrieve + fan-out and cite community/social…
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `evals/evals.json`, `references/audit-and-measurement.md` and `references/examples.md`).
It sits in Marketing & SEO, covering AI search optimization. It works with OpenAI, Perplexity, Wikipedia and Reddit. The repository describes itself as: 106 social media skills for AI agents - strategy, writing, video, design, platform growth, publishing, and analytics. Works with Claude, Cursor, OpenClaw, Hermes & 40+ agents. The licence is MIT.
When your agent uses it
- Get cited by ChatGPT/Perplexity/Google AI
- Answer engine optimization (AEO)
- Will AI recommend my brand
- Wants to show up in AI-generated answers
Example prompts
- “get cited by ChatGPT/Perplexity/Google AI,”
- “ChatGPT SEO,”
- “LLM SEO / LLMO,”
- “/ai-search-optimization”
Workflow steps
7 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 6e30eeb. 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
AI Search Optimization loads about 2k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 251 tokens; SKILL.md has 837 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 social-media-skills/skills at commit 6e30eeb, republished under its MIT licence (© social-media-skills). 837 words, ~2,022 tokens.
Download SKILL.mdSave it as
.claude/skills/ai-search-optimization/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.- name
- ai-search-optimization
- description
- Use to get a brand and its content CITED and RECOMMENDED by AI answer engines — the GEO (Generative Engine Optimization) / AI-search-visibility skill. Run when the user says "GEO," "get cited by ChatGPT/Perplexity/Google AI," "ChatGPT SEO," "LLM SEO / LLMO," "AI Overviews," "answer engine optimization (AEO)," "will AI recommend my brand," or wants to show up in AI-generated answers, not just the feed or Google links. Reads brand-profile and audience first. AI engines retrieve + fan-out and cite community/social sources heavily (Reddit, YouTube, Wikipedia); platforms disagree; earned media beats product pages; extractable, fresh content drives citation. Covers the four GEO levers (retrievable, earned mentions, extractable content, entity clarity), authentic social plays, and the manual prompt-audit method. Refuses astroturfing; never fabricates "share of voice." Sibling of social-seo (platform + Google search). Judges via the audit + GEO tools + AI referral traffic.
- metadata.version
- 1.0.0
- license
- MIT
AI Search Optimization (GEO)
Get your brand into the answer when people ask ChatGPT, Perplexity, Google AI, Gemini, or Copilot a question in your space — instead of watching a competitor get named. This is GEO (Generative Engine Optimization; also AEO/LLMO): optimizing to be cited and recommended by AI engines. It supplements search/SEO; it doesn't replace it.
Four truths shape everything:
- AI answers are built by retrieval + fan-out. Engines retrieve live from search indexes (ChatGPT via OpenAI's own crawler/index, OAI-SearchBot — historically Bing-seeded; Google feeds AI Overviews/AI Mode) and split your topic into sub-queries — so ranking in search feeds AI citation, and you optimize for a constellation of questions.
- AI cites community/social sources most. Reddit, YouTube, Wikipedia, LinkedIn, listicles and review sites dominate citations — the cited pages are usually not your pages. Earned mentions beat product pages.
- Platforms disagree. ChatGPT skews Wikipedia, Perplexity skews Reddit, AI Overviews lean on E-E-A-T + the community web. Optimizing for one ≠ all.
- Extractable, fresh, well-sourced content gets quoted. Quotations, statistics, citations, Q&A structure, and schema lift citation; stale content gets displaced.
(Full mechanics: references/how-ai-engines-cite.md.)
Step 0 — Read the foundation + the goal
Load brand-profile.md and audience.md (entity clarity + the real questions matter). Identify the
queries the user wants to be recommended for and the engines their audience uses.
Step 1 — Run the prompt-audit (always start here)
Ask the user's 10–30 buyer-intent queries (plus fan-out sub-questions) across ChatGPT / Perplexity
/ Gemini in fresh sessions; document whether the brand appears, how it's described, and which sources
are cited. The cited sources are the strategy; the gaps are the content list. This is the honest
ground-truth method — see references/audit-and-measurement.md.
Step 2 — Be retrievable (the foundation)
If you can't be found in search, you can't be cited: rank in Google/Bing and in platform search →
social-seo (the sibling). Same keyword/question research powers both. And verify AI retrieval
crawlers can reach the site — robots.txt and CDN/bot-protection defaults (e.g. Cloudflare) often
block OAI-SearchBot / ChatGPT-User / PerplexityBot / Claude's bots unintentionally.
Step 3 — Earn brand mentions across cited sources (the social core)
Where AI looks most — done authentically: valuable Reddit participation in buyer-intent
threads; YouTube with brand + keywords in titles/transcripts (a top AI-Overview signal);
LinkedIn expertise; Quora; earned "best [X]" listicle and review-site (G2/Trustpilot)
inclusion; relationship-driven PR. The goal is a web of mutual verification. See
references/the-geo-levers.md.
Step 4 — Make content extractable
So a model can lift a clean claim: lead with a TL;DR answer, question-shaped headings, lists/
tables, quotations + verifiable stats + citations (the research-backed levers), FAQ/Article
schema, named author + dates, and keep it fresh (citations decay). (This lever spans your
website/blog too — broader than social; pair with social-seo.)
Step 5 — Build entity clarity
Give the model a clean entity to recommend: a consistent one-line description across site/profiles/
listings → brand-profile; Wikipedia/Wikidata if genuinely notable; claimed listings + consistent
NAP; a corroborated "the X for Y" position.
Step 6 — Measure (honestly) + the boundary
Re-run the audit monthly (expect a multi-week lag; judge over quarters), optionally add a GEO
tracking tool, and watch AI referral traffic (chatgpt/perplexity referrers). Never fabricate a
"share of voice" or citation %. No WoopSocial analytics. Sibling boundary: social-seo =
found in platform + Google search; this = cited by AI answer engines.
Show full SKILL.md (312 more words)Show less
Orchestration map
ai-search-optimization sets the AI-visibility layer; it routes to / pairs with: social-seo
(retrieval/search foundation — sibling) · brand-profile (entity) · content-pillars (question
clusters) · reels-script / the growth skills (the YouTube/Reddit/LinkedIn content that earns
mentions) · viral-reverse-engineering (what gets cited/shared) · scheduling-and-queue (publish).
Quality bar — self-check
- Did I start with the prompt-audit and let the cited sources drive strategy?
- Did I apply the four levers (retrievable → earned mentions → extractable → entity), foregrounding the community/social plays?
- Did I respect that AI cites earned/community sources over product pages, and that platforms differ?
- Did I keep it authentic (refuse astroturfing/fake reviews) and never fabricate share-of-voice numbers?
- Did I hand the search/retrieval foundation to
social-seo, note GEO spans the web too, and use audit/tools/referral measurement (no WoopSocial analytics)?
Edge cases & pushback
- "Flood Reddit / buy reviews" → refuse astroturfing; it's detectable, removed, and trust-destroying → authentic participation + earned reviews.
- "Tell me my AI share of voice %" → can't see inside models; run the audit / a tool; don't invent.
- "Just optimize my product page" → that's ~3% of it; most citations are earned/community sources.
- "Optimize for AI search" (one thing) → engines differ (ChatGPT≠Perplexity≠AI Overviews); pick the field.
- "Is this my TikTok/Google SEO?" → related but distinct →
social-seoowns platform/Google search. - "Does WoopSocial track this?" → no; measure via audit + GEO tools + referral analytics.
- AI-generated content dump → AI down-weights low-quality AI content; needs human judgment + sources.
Related skills
social-seo— the sibling: platform + Google search (the retrieval foundation AI pulls from).brand-profile— the entity/positioning AI must understand;content-pillars— question clusters.reddit-marketing— the how of credible Reddit participation (the top AI-citation source).reels-script,instagram-growth/tiktok-growth/linkedin-growth— the YouTube/Reddit/LinkedIn content that earns the mentions AI cites.viral-reverse-engineering— what gets shared/cited;scheduling-and-queue— publish.
References
references/how-ai-engines-cite.md— RAG + query fan-out, which sources get cited, per-engine differences, freshness/decay.references/the-geo-levers.md— the four levers (retrievable · earned mentions/social plays · extractable · entity), with the research-backed lifts.references/audit-and-measurement.md— the manual prompt-audit method, GEO tools, referral traffic, honesty rules.references/examples.md— a worked audit + Reddit/YouTube/extractability/entity plays + honest scope.
© social-media-skills, 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 5 other files (references) in skills/ai-search-optimization of social-media-skills/skills.
- SKILL.md
- evals/evals.json
- references/audit-and-measurement.md
- references/examples.md
- references/how-ai-engines-cite.md
- references/the-geo-levers.md
Open the folder on GitHubat commit 6e30eeb
Compare with similar skills
AI Search Optimization 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 |
|---|---|---|---|---|---|---|
| AI Search Optimization this skillsocial-media-skills/skills | 134 | — | ~2k | Automated safety check: Pass | MIT | |
| Blog StrategyAgriciDaniel/claude-blog | 2.3k | — | ~4.4k | Automated safety check: Pass | MIT | |
| Blog StrategyInfrasity-Labs/dev-gtm-claude-skills | 136 | — | ~3.8k | Automated safety check: Pass | MIT | |
| Geo Optimizationfabricioctelles/skills | 106 | — | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| SEO AgiLeoYeAI/openclaw-master-skills | 2.2k | — | ~6.4k | Automated safety check: Notes | MIT | |
| Geo Fundamentalswasp-lang/wasp | 19k | 9 repos | ~861 | Automated safety check: Pass | MIT |
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Related
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Questions about AI Search Optimization
What does AI Search Optimization do?
A skill your agent uses to get a brand and its content CITED and RECOMMENDED by AI answer engines — the GEO (Generative Engine Optimization) / AI-search-visibility skill. AI Search Optimization is an agent skill from social-media-skills/skills. Use to get a brand and its content CITED and RECOMMENDED by AI answer engines — the GEO (Generative Engine Optimization) / AI-search-visibility skill.
When should I use AI Search Optimization?
AI Search Optimization fits situations like: get cited by ChatGPT/Perplexity/Google AI; answer engine optimization (AEO); will AI recommend my brand; wants to show up in AI-generated answers.
How do I install AI Search Optimization in Claude Code?
Run `npx skills add social-media-skills/skills --skill ai-search-optimization -a claude-code`. Or copy the skill folder (skills/ai-search-optimization in social-media-skills/skills) into .claude/skills/ai-search-optimization in your project. Claude Code loads it when a task matches its description.
How do I install AI Search Optimization in Codex?
Run `npx skills add social-media-skills/skills --skill ai-search-optimization -a codex`. Or copy the skill folder (skills/ai-search-optimization in social-media-skills/skills) into .agents/skills/ai-search-optimization in your project. Codex loads it when a task matches its description.
Can I use AI Search Optimization 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 social-media-skills/skills --skill ai-search-optimization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-search-optimization, .gemini/skills/ai-search-optimization, .github/skills/ai-search-optimization and .opencode/skills/ai-search-optimization in your project.
What does AI Search Optimization need to run?
SKILL.md names no scripts, command-line tools or credentials: AI Search Optimization is instructions for the agent only.
Does AI Search Optimization 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 AI Search Optimization 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 AI Search Optimization use?
AI Search Optimization 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 AI Search Optimization use?
About 2k tokens (SKILL.md is roughly 8.1k 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 4.3k tokens, read only when the agent opens those files.
What are the alternatives to AI Search Optimization?
Skills that share tags, products or a category with AI Search Optimization: Blog Strategy (AgriciDaniel/claude-blog, 2.3k stars), Blog Strategy (Infrasity-Labs/dev-gtm-claude-skills, 136 stars), Geo Optimization (fabricioctelles/skills, 106 stars) and SEO Agi (LeoYeAI/openclaw-master-skills, 2.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AI Search Optimization?
social-media-skills (a GitHub organization) maintains it in social-media-skills/skills, which has 134 GitHub stars. The repository holds 106 skills in this directory. The repository was last updated on October 1, 2026.
Source: social-media-skills/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.