The on_page/content_parsing/live endpoint returns headings inside
main_topic[] / secondary_topic[] arrays (each with h_title + level),
not as flat h1/h2/h3 arrays. Old extractor looked for keys that don't
exist, so every research run reported Avg H2s: 0 / Avg H3s: 0
regardless of competitor depth. Word count and title were broken for
the same reason.
Fixes:
- _extract_headings now walks main_topic + secondary_topic by level
- _count_words computes from page_as_markdown with topic-text fallback
- _extract_title pulls H1 from markdown, falls back to main_topic[0]
- Replaced regression test that was asserting the broken shape
- Added 7 new tests covering the real DataForSEO response
Verified live: SpotHero JFK page now extracts 19 headings (11 H2 + 8 H3)
where it previously returned 0. Full pipeline: Avg H2s 9.2 / Avg H3s 3.5.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
GEO framework that writes pages ranking on Google AND getting cited by
LLMs. 500-token chunk architecture, Reddit Test quality gates,
verification tags, Not For You blocks, information gain enforcement.
Data layer: DataForSEO, GSC, Ahrefs MCP, SEMRush MCP.
21 files, all tests passing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
