aeo-kit

Zero-Click AEO toolkit — turn any document, file, or website into LLM-readable Markdown + an llms.txt outline, then index and search it locally. A thin, clean composition of best-in-class open-source parts; it does not reinvent conversion, compression, or vector indexing.

crawl  → ingest → index → search
(site)   (md +    (turbovec) (top-k)
          llms.txt)

Why

"AI Engine Optimization" (AEO/GEO) starts with getting messy real-world content into a form a model can use. aeo-kit composes:

• markitdown (MIT) — PDF/DOCX/PPTX/XLSX/HTML/CSV → Markdown
• headroom-ai (Apache-2.0, optional) — compress verbose tool/RAG context 60–95%
• turbovec — air-gapped quantized vector index
• a tiny zero-dependency crawler (no AGPL, no hosted API key)

Everything runs locally. No API keys required.

Install

pip install aeo-kit            # core
pip install "aeo-kit[compress]"  # + headroom-ai for context compression

CLI

# 1) crawl a site (local interlinked html or a live URL) -> markdown
aeo-crawl ./site/index.html --out build/site
aeo-crawl https://example.com --max-pages 5 --out build/site

# 2) ingest any file / folder / URL -> per-doc md + site-level llms.txt
aeo-ingest ./company_docs --out build/aeo --compress

# 3) local retrieval over the ingested docs (TF-IDF -> turbovec)
aeo-search build/site "consumption tax filing" --k 3

Library

from adapters import markitdown_aeo as mk
conv = mk.convert("page.html")
print(mk.aeo_extract(conv))     # llms.txt seed from the heading structure

Notes

• Crawler politeness: HTTP mode is same-domain only, respects robots.txt, rate-limits, and is bounded by --max-pages / --max-depth.
• Search scope: aeo-search uses TF-IDF (lexical) retrieval over turbovec — no embedding model / network required. Swap in a sentence-transformer for semantic search; the turbovec layer is unchanged.
• Compression: headroom-ai protects user messages and compresses tool/log/RAG content; clean short prose may compress little, by design.

Develop

pip install -e .
python experiment.py   # end-to-end real run -> poc/out/
python audit.py        # deterministic checks (exit 0 = all pass)

License

MIT (this toolkit). Bundled dependencies are installed separately and retain their own licenses — see THIRD_PARTY_NOTICES.md.