mcpField
S
seo-geo-answerblocks

seo-geo-answerblocks

github.com/hainrixzMarketing & growth79202 installsUpdated 4d ago
Repository

About seo-geo-answerblocks

seo-geo-answerblocks is an SEO audit skill that checks whether page passages can be extracted and understood on their own. It suggests human-reviewed structural edits without silently rewriting published content or inventing claims.

Key features

  1. 01Checks direct answers after headings
  2. 02Assesses standalone passage clarity
  3. 03Reviews lists, tables, and definitions
  4. 04Checks question headings and summaries
  5. 05Drafts edits for human review

Use cases

  1. 01Find question headings without direct answers
  2. 02Spot passages that depend on prior context
  3. 03Add summary blocks to long-form pages

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/hainrixz/claude-seo-ai --skill seo-geo-answerblocks

After installing, type/seo-geo-answerblocksin Claude Code to confirm it loaded.

Details

From the project README

seo-geo-answerblocks (M11)

AI engines cite passages they can lift whole, without surrounding context — so passage structure is the highest-leverage on-page AI signal. This module checks extractability; for who is allowed to fetch and cite the page, see references/ai-crawlers.md.

Inputs

Work from the PageSnapshot named in your dispatch envelope: read parsed from <run_dir>/pages/<slug>.json (headings[], text_sample, word_count) — passages come from the HTML file, not from a summary; Grep pages/<slug>.html for verbatim evidence; site artifacts live in <run_dir>/site/{robots.json,sitemaps.json,discovery.json}. Deterministic findings already emitted by audit.mjs are listed in <run_dir>/findings.deterministic.json — do not re-emit those ids; add model-judged findings only. If invoked directly with a URL/path and no snapshot exists, first run node "${CLAUDE_PLUGIN_ROOT}/scripts/snapshot.mjs" <target> --out "${CLAUDE_PLUGIN_DATA}/runs" and use the printed snapshot path.

Audits

Working from the PageSnapshot (parsed_rendered when render.used is not none, else parsed):

  1. Heading → direct answer: for each H2/H3 that reads as a question (or implies one), is the first paragraph a direct, ~40-60 word answer — not a windup ("In this section we'll explore…")?
  2. Self-contained passages: are top-level passages ~134-167 words and answerable on their own? Flag unresolved anaphora ("as mentioned above", "this", "the latter") that needs prior context to parse.
  3. Structured forms: presence of lists, comparison tables, and explicit term definitions where the content warrants them — these are disproportionately quoted.
  4. Question-shaped headings: do headings phrase real user questions (how/what/why/when), matching likely prompts?
  5. TL;DR / summary blocks: an up-front summary or key-takeaways block the engine can extract verbatim.
  6. Semantic completeness: can each passage answer its heading with zero external context — the strongest single correlate of AI citation, and the heaviest check in this module (it carries the most weight, but it never caps the score — see Findings).

Fixes

  • PROPOSED: answer-block rewrites (heading → tight 40-60 word lead) and TL;DR drafts, generated from existing page content, surfaced one item at a time for the user to accept/edit. Each becomes a fix_preview diff only after acceptance.
  • ADVISORY: structural suggestions ("split this 400-word passage", "add a definition list here") where intent is editorial.
  • Never silently rewrite published prose, and never invent facts to fill a passage — if a claim is missing leave a clearly-marked TODO placeholder for the user. No finding here is auto.

Verification

  • Method is manual_review. The deterministic part is reproducible offline: word-count windows (answer 40-60w; passage 134-167w), question-heading detection, anaphora openers, and TL;DR presence via node "${CLAUDE_PLUGIN_ROOT}/scripts/check-answerblocks.mjs" --snapshot <pages/<slug>.json> [--lang en|es|auto] (or --url <u> / --file <path>). Use manual_review as the finding's verification.method (the enum has no heuristic value); the script is the verification.reproduce command.
  • Language coverage: the heuristics ship EN and ES lexicons (question words including ¿, windup openers, anaphora, TL;DR/Resumen markers). When the detected language is neither, the language-dependent fields come back null — never 0 — and the finding is manual_review, so a page in an unsupported language is never scored as a clean pass.
  • Semantic completeness and anaphora resolution still require a judgment pass; when that pass or the rendered DOM is unavailable, status is needs_api (or manual_review), never a false pass.

Findings

Findings conform to schema/finding.schema.json; axis ai. Severity policy: 5 is reserved for catastrophic, eligibility-killing facts at site/template scope; 4 major · 3 moderate · 2 minor · 1 cosmetic · 0 informational — and only an established severity-5 fail in an active category can cap a score (references/scoring-model.md). Nothing in M11 is established, so nothing here ever caps.

  • M11.heading.no_direct_answer — a question H2/H3 followed by a windup instead of an answer (fail, severity 3, fixable: proposed, confidence directional).
  • M11.passage.unresolved_anaphora — a passage opens with "As mentioned above…" / "Esto…" and cannot be read standalone (warn, severity 2, fixable: proposed, confidence directional).
  • M11.passage.overlong — a passage runs well past the extractable window (>167 words) with no internal structure to lift (warn, severity 2, fixable: proposed, confidence directional).
  • M11.summary.missing_tldr — no up-front summary / key-takeaways block on a long-form page (warn, severity 2, fixable: proposed, confidence directional).
  • M11.answers.ok — question headings are answered directly and passages are self-contained (pass, severity 3, confidence directional).
  • M11.lang.unsupported — the page language is outside the EN/ES lexicons, so the passage heuristics cannot decide (manual_review, severity 0; language-dependent fields null). Each finding's evidence.observed quotes the page (heading text + first sentence, or the offending clause) and verification.reproduce is the runnable command above; expected_impact is banded + confidence-tagged with no naked percentage.

Honesty

  • Google does not ask for AI-specific rewriting or chunking. Its generative-AI guidance points back at the same fundamentals — indexable, snippet-eligible, well-structured pages written for people — and it publishes no passage length, no "chunk size", and no answer-block format. Everything in this module is a readability and extractability argument that also helps human readers; say that, and never sell a rewrite as an engine requirement.
  • Word-count windows are heuristics from observed citation patterns, not engine-published thresholds — they are directional, never established; flag a passage, don't hard-fail purely on length.
  • Adding a "TL;DR" label or bolting question marks onto headings does nothing if the passage still cannot answer standalone. Semantic completeness is what carries weight; formatting theatre is a myth this tool does not ship.
  • The heuristics are language-bound. On an unsupported language the honest output is manual_review, not a pass — a silent zero would read as "no problems found".

Comments

Markdown supported