seo-geo-factdensity

seo-geo-factdensity (M12)

Generative engines preferentially cite passages that are concrete, quantified, and attributable. This module measures how "citable" the page's prose is — facts, numbers, original data, and authoritative outbound links — not vocabulary. AI retrieval/citation context: references/ai-crawlers.md.

Audits

Working from the PageSnapshot (rendered_dom if present, else raw_html):

1. Statistic/number density per passage: tokenize the main content into passages (paragraph / <li> / heading-bounded block) and count numeric tokens — figures, percentages, dates, quantities, ranges. Flag long passages of pure assertion with zero numeric support.
2. Proprietary/original data: detect first-party-data signals — patterns like "our study", "our survey", "our data", "we analyzed", "we surveyed", "in our test", "internal data" — and note whether such claims are backed by a method/sample, a table, or a chart.
3. Outbound citations: count outbound links from the main content to authoritative sources (standards bodies, primary research, official docs, .gov/.edu, named publications); distinguish them from internal/nav/affiliate links.
4. Claim-without-source flags: detect strong factual or comparative claims ("the most", "fastest", "studies show", superlatives, hard numbers) that carry no inline citation or data reference, and mark each as a candidate for sourcing.

Fixes (fixable: advisory)

ADVISORY only — this module proposes nothing it would write. It produces a list of (a) claims that should carry a statistic or citation, (b) passages where an original-data callout (table, "our data" box, methodology note) would raise citability, and (c) unsupported superlatives to soften or source. The tool will NOT fabricate statistics, sample sizes, study results, or source URLs. Where a value is missing, it emits a clearly-marked TODO placeholder for the user to fill — never an invented number. (Findings here are fixable: advisory per the finding schema.)

Verification

• Heuristic: manual_review plus deterministic counts — numeric-token density per passage and outbound-authority link count — computed from the snapshot. Report the raw counts so a human can re-derive them.
• Judgment calls (is this claim "strong"? is this source "authoritative"?) require manual_review; do not auto-pass them.
• When the content tier or rendered DOM needed to count passages reliably is unavailable, status is needs_api, never a false pass.

Findings

Emit findings per schema/finding.schema.json. Examples:

• M12.density.low_numeric_passages — multiple main-content passages with zero numeric support (status warn, severity 4, fixable: advisory, axis ai, confidence directional).
• M12.citations.no_outbound_authority — main content makes factual claims but links to zero authoritative outbound sources (status warn, severity 4, fixable: advisory, axis ai, confidence directional).
• M12.claim.unsourced_superlative — a superlative/comparative claim with no inline citation or data (status warn, severity 1, fixable: advisory, axis ai, confidence speculative).

Each finding: evidence.observed quotes the exact passage/claim from the page; verification.reproduce is the runnable count (e.g. node scripts/factdensity.mjs --url <u>); expected_impact is banded + confidence-tagged (no naked %).

Honesty

• Refuse "AI-specific keyword" rewrites — there is no magic vocabulary that wins citations. Citability comes from extractable structure, verifiable facts, and demonstrable authority, not phrasing tricks.
• Never invent a statistic, sample size, or source to "fill" a flagged claim. Quantification only helps if it is true and attributable; a fabricated number is a liability, not a win.
• Density is a means, not an end — flag stuffing numbers into prose that doesn't warrant them as its own anti-pattern.