Cherry-picked from claude-seo (github.com/AgriciDaniel/claude-seo, MIT)
content_quality.py, rewritten to the lib/seo-data contract per BDR-070. The
Content Shape axis was 100% LLM judgement; this gives it a measured input.
fetch.sh content_quality (stdin or --file) → {filler_score, ai_pattern_score,
information_density, overall_quality, flags[], matches{}}. 100% deterministic:
QRG §4.6 filler list (26 phrases) + AI-pattern list (46) kept intact, regex
matching, no LLM. Stdlib only (argparse/json/re/sys/collections/typing).
Advisory, NOT a verdict — the point of the wiring. It never claims a page "is
AI-written" (LRN-131/133); flags are candidates for human review. geo-analyzer
STEP 8 Check 10 makes it a deterministic input that INFORMS checks 1-9, never
replaces them, never scored on its own. A low number is not an automatic
finding.
Detection proven both directions (a detector that always- or never-flags is
useless): filler+slop text → flags [filler, low-density], overall 34-49; clean
dense factual text (dates/EUR/percentages) → no flags, overall 90. Empty input →
degraded/empty_input, never zeros-as-a-result.
Verified: GATE 1 verifier CONFORME 10/10 (both directions exercised live, lists
diffed intact vs source, advisory language confirmed); GATE 2 self-scan clean
(only sink is read-only open() for --file); seo-data 190 → 210 pass, 0 fail;
full suite green; shellcheck + py_compile clean.
