Fire Your SEO Agency Agent Skill

by leopard627• 987•• Scanned•Claim this listing•Request removal
SEO & AI Searchaeoai searchclaude codeclaude skillsgeo

Fire your SEO·GEO agency 🔥 A Claude Code skill that audits and optimizes SEO·AEO·GEO·LLMO·NEO(Naver) by itself — 월 50~350만 원짜리 'AI 검색 최적화' 대행, AI 에이전트가 대체합니다

Fire Your SEO Agency is an open-source agent skill by leopard627, written mainly in Python, with 987 GitHub stars and the MIT license. Its code was last updated Sep 25, 2026.

🔥 fire-your-seo-agency

한국어 · English

GitHub stars GitHub forks Latest release License: MIT

fire-your-seo-agency

Paying $400–$2,500/month for an SEO or "AI visibility" agency? Fire them. Your AI agent can do the work.

A wave of services now charges monthly retainers for "AI-era search optimization", "guaranteed ChatGPT citations", and "LLM visibility". Most of what they actually do is public standards and repeatable checklists. When a human does it, it's a retainer. When your agent does it, it's a skill.

This repository is a Claude Code skill. Install it and your agent audits your site, fixes what's broken, and measures the results.

Built on real numbers

This is not theory. The same playbook, applied to Chickenstock — a solo-built Korean stock research service:

  • 1.54M search impressions in 30 days (+85,578% MoM), 7.4K clicks
  • Pages cited paragraph-by-paragraph by Naver's AI Briefing (Korea's answer engine)
  • Zero ad spend — all inbound from search and AI citations

The journey is documented publicly on Threads @kindainvestor.

The five lanes

"Search optimization" means different things to different engines. This skill treats them as five distinct lanes:

LaneTargetThe question it answers
SEOGoogle & Bing crawlersCan crawlers read and index my content at all?
AEO (Answer Engine)Google AI Overviews, Bing CopilotDoes the AI answer box above the results cite me?
GEO (Generative Engine)ChatGPT, Perplexity, ClaudeWhen generative AI browses, am I the primary source?
LLMO (LLM Optimization)The model's own knowledgeDoes the model know my brand — and know it correctly?
NEO (Naver Engine)Naver search & AI BriefingHalf of the Korean market — does Naver cite me?

NEO is what makes this skill different. Global AEO guides ignore Naver entirely, but if you serve the Korean market, half your traffic lives there.

Plus a content engine. Most of a retainer pays for "N posts a month". This skill replaces that with a pipeline: a question backlog pulled from your own search data, a frontmatter content model that generates the JSON-LD, a publish gate every post must pass, and a refresh/merge policy so posts don't rot. Output is measured as "posts that get seen and cited", not "posts published".

Install

As a plugin (recommended — one command, easy updates):

/plugin marketplace add leopard627/fire-your-seo-agency
/plugin install fire-your-seo-agency@fire-your-seo-agency

Or via git clone:

# As a project skill (this project only)
git clone https://github.com/leopard627/fire-your-seo-agency.git .claude/skills/fire-your-seo-agency

# Or as a personal skill (every project)
git clone https://github.com/leopard627/fire-your-seo-agency.git ~/.claude/skills/fire-your-seo-agency

For Codex, put it under .agents/skills (no need to commit a copy into your repo):

git clone https://github.com/leopard627/fire-your-seo-agency.git .agents/skills/fire-your-seo-agency   # project
git clone https://github.com/leopard627/fire-your-seo-agency.git ~/.agents/skills/fire-your-seo-agency # personal

Then in Claude Code:

/fire-your-seo-agency audit my site

Your agent starts with a crawler-eye audit and returns a scorecard like this before touching anything:

LaneStatusEvidence
SEO⚠️Body is SSR'd, but 214 detail pages missing from sitemap
AEO❌No direct-answer first paragraphs; FAQ structured data: 0
GEO❌No llms.txt; GPTBot/PerplexityBot policy undecided in robots.txt
LLMO⚠️Brand name spelled 3 different ways across surfaces
NEO❌Not registered in Naver Search Advisor

…then proposes priorities, implements them, and schedules the re-measurement.

What it does

  1. Audit — reads your site the way a crawler does (no JavaScript) and scores all five lanes
  2. Technical base — fixes SSR exposure, sitemaps, meta, structured data
  3. Intent landing pages — designs pages on the "one question = one page" principle
  4. Machine readability — llms.txt, JSON-LD, citation-ready paragraph structure
  5. Naver — from Search Advisor registration to AI Briefing citation requirements
  6. Content engine — sub-blog setup, question backlog, publish gate, refresh & merge policy
  7. Measurement loop — schedules a re-measurement and proves the change with numbers

What it refuses to do

  • ❌ Buying backlinks, engagement pods, content spam — we don't fight the search engine
  • ❌ "Guaranteed rankings" promises — no claims without measurement
  • ❌ Keyword stuffing, hidden text, cloaking — nothing that gets your domain killed

The whole philosophy fits in one line: AI doesn't cite good writing. AI cites accurate data. Become the primary source for a number, and the citations follow.

Structure

SKILL.md              ← agent operating procedure (audit → implement → measure)
references/
  seo.md              ← technical SEO checklist + real-world traps
  aeo.md              ← answer engine optimization (Bing WMT · AI Overviews · Copilot · E-E-A-T)
  geo.md              ← generative engine optimization (AI crawler policy · llms.txt · primary source)
  llmo.md             ← model-knowledge optimization (brand entity)
  neo-naver.md        ← Naver (Search Advisor · AI Briefing · blog two-track)
  content.md          ← content ops (sub-blog · content model · backlog · publish gate · refresh)
  measure.md          ← the measurement loop (fixing it is not the finish line)
  en/                 ← English mirrors of all reference docs (for human readers)
.claude-plugin/       ← plugin & marketplace manifests (/plugin install support)
tools/                ← repository checks (validate.py) + outbound domain allowlist
tests/                ← unit tests for the checks
.github/workflows/    ← CI: checks and tests on every push/PR, monthly crawler-table freshness

The Korean documents under references/ are canonical (the agent reads those); references/en/ mirrors them in English for human readers.

Repository checks

.github/workflows/validate.yml runs these on every push and pull request (standard library only):

python3 tools/validate.py                   # repository checks
python3 -m unittest discover -s tests -t .  # tests for the checker
python3 tools/validate.py --max-age 100     # is the crawler table older than 100 days? (monthly)
  • Domains — every outbound URL or domain in the docs must be on tools/allowed-domains.txt; a new domain only gets in through a diff to that file
  • Crawlers — the AI crawler table in geo.md and the log command in measure.md cover the same user agents, in both languages
  • Release — SKILL.md, plugin.json, marketplace.json and CHANGELOG.md agree on name and version
  • Mirror — each English mirror keeps the Korean original's structure (headings, section numbers, tables, checkboxes) and cites the same outbound hosts
  • Links and skill — relative links, anchors and path mentions resolve; SKILL.md frontmatter limits

Contribution rules are in CONTRIBUTING.md.

Star History

<a href="https://www.star-history.com/#leopard627/fire-your-seo-agency&Date"> <picture> <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=leopard627/fire-your-seo-agency&type=Date&theme=dark" /> <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=leopard627/fire-your-seo-agency&type=Date" /> <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=leopard627/fire-your-seo-agency&type=Date" /> </picture> </a>

License

MIT — use it freely, and keep the retainer money.

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