pythia-geo 0.2.1

The oracle that tells you how AIs see your site — GEO/AEO audit CLI

Pythia

The oracle that tells you how AIs see your site.

Pythia is a local-first CLI that audits any webpage for GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) — making sure AI systems like ChatGPT, Claude, Perplexity, and Mistral can read, cite, and recommend your content.

No API key. No SaaS. No cloud account. Works on any public URL. Pipe it into CI/CD and fail the build if your GEO score drops below threshold.

pip install pythia-geo
pythia audit https://example.com

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Why GEO matters

Traditional SEO optimizes for crawlers. GEO optimizes for large language models that summarize, answer, and cite web content directly in their responses. If your site isn't structured for AI comprehension, you're invisible to a growing share of user queries.

Pythia checks 14 signals across three categories:

Category	Weight	What it covers
Structure	40%	llms.txt, robots.txt bot policies, sitemap, JSON-LD
HTML	30%	H1 uniqueness, heading hierarchy, title, meta description, OpenGraph
Content	30%	Generic headings, FAQ patterns, E-E-A-T signals, structured lists

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Quick start

# Audit a URL, print Markdown report
pythia audit https://example.com

# JSON output for CI integration
pythia audit https://example.com --format json

# French output
pythia audit https://example.com --lang fr

# Fail if score < 80 (default threshold: 70)
pythia audit https://example.com --threshold 80

# Save report to file
pythia audit https://example.com --output report.md

# List all available checks
pythia list-checks

Exit code: 0 if score ≥ threshold, 1 otherwise.

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CI/CD integration

# .github/workflows/geo-audit.yml
- name: GEO audit
  run: |
    pip install pythia-geo
    pythia audit https://yoursite.com --threshold 70 --format json --output geo-report.json

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Sample output

# Pythia GEO Audit — https://example.com

Score: 74/100  ●●●●●●●○○○  ❌ FAIL (threshold: 70)

## STRUCTURE (40%)  —  32/100

- ✅ PASS `llms_txt_present` — llms.txt found and accessible
- ⚠️  WARN `llms_full_txt_present` — llms-full.txt not found (optional but recommended)
- ✅ PASS `robots_ai_bots` — No AI bots blocked in robots.txt
- ✅ PASS `sitemap_accessible` — Sitemap found and accessible
- ❌ FAIL `jsonld_present_valid` — No JSON-LD structured data found

## HTML (30%)  —  25/100

- ✅ PASS `single_h1` — Exactly one H1 found
- ✅ PASS `heading_hierarchy` — Heading hierarchy is sequential
- ✅ PASS `title_length` — Title length is within 30–65 characters
- ⚠️  WARN `meta_description` — Meta description present but length is outside 70–160 characters
- ❌ FAIL `opengraph_minimal` — No OpenGraph tags found

## CONTENT (30%)  —  17/100

- ✅ PASS `generic_headings` — No generic headings detected
- ⚠️  WARN `faq_pattern` — No FAQ structure found
- ✅ PASS `eeat_signals` — Author and publication date detected
- ❌ FAIL `structured_content` — No structured content found (no lists or tables)

## Recommendations

- **`jsonld_present_valid`** — Add <script type="application/ld+json"> with Organization or Article schema
- **`opengraph_minimal`** — Add og:title, og:description, og:type meta tags
- **`structured_content`** — Use <ul>, <ol>, or <table> to structure your content

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Checks reference

#	ID	Category	PASS	WARN	FAIL
1	llms_txt_present	structure	/llms.txt accessible	—	missing or empty
2	llms_full_txt_present	structure	/llms-full.txt accessible	missing	—
3	robots_ai_bots	structure	no AI bots blocked	robots.txt missing	≥1 bot blocked
4	sitemap_accessible	structure	sitemap found	—	not found
5	jsonld_present_valid	structure	valid JSON-LD found	malformed JSON	none
6	single_h1	html	exactly 1 H1	>1 H1	no H1
7	heading_hierarchy	html	no level gaps	—	≥1 gap
8	title_length	html	30–65 chars	out of range	missing
9	meta_description	html	70–160 chars	out of range	missing
10	opengraph_minimal	html	og:title + og:description + og:type	1–2 missing	none
11	generic_headings	content	0 generic	1–2 in H2+	H1 generic or ≥3
12	faq_pattern	content	FAQ detected	none found	—
13	eeat_signals	content	author + date	one of two	neither
14	structured_content	content	≥1 list or table	—	none

AI bots checked by robots_ai_bots: GPTBot, ClaudeBot, PerplexityBot, Google-Extended, CCBot, MistralAI-User.

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About the name

In ancient Greece, Pythia was the Oracle of Delphi — the high priestess of Apollo who delivered prophecies to kings, generals, and philosophers. Seekers traveled from across the Mediterranean to ask her questions and receive pivotal answers that shaped history.

Today, LLMs are the new oracles. Ask ChatGPT about a product, a concept, a brand — and it will answer with the confidence of a Delphic prophecy. Whether your site appears in that answer, and how accurately it's represented, depends entirely on how well your content speaks to these modern oracles.

Pythia ensures the oracle speaks your truth.

The name also fits the Kryptide ecosystem: kryptos (κρυπτός) means "hidden" in Greek — Pythia is the one who reveals.

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Contributing

Issues and PRs welcome. See the project conventions in CLAUDE.md.

Commit messages follow Conventional Commits: feat:, fix:, docs:, test:, chore:.

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License

MIT — see LICENSE.

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🇫🇷 En français

Pythia est un CLI Python qui audite n'importe quelle page web pour le GEO (Generative Engine Optimization) — l'optimisation pour les moteurs de réponse IA comme ChatGPT, Claude, Perplexity et Mistral.

Sans clé API. Sans SaaS. Fonctionne en local ou en CI/CD.

pip install pythia-geo
pythia audit https://monsite.fr --lang fr

14 vérifications réparties en trois catégories : structure (40%), HTML (30%), contenu (30%). Score sur 100. Seuil configurable (défaut : 70). Code de sortie 1 si sous le seuil.