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Marketing i treści · Przegląd i audyt

geo

/geo

Ocenia widoczność strony w wyszukiwaniu AI (GEO/AEO): możliwość wyciągnięcia odpowiedzi, gęstość faktów, dostęp crawlerów AI i encje, z wynikiem AI Visibility, tylko do odczytu.

Repozytorium
claude-seo-ai ↗
Licencja
MIT
Ostatnia zmiana repozytorium
25.10.2026

Ocena i bezpieczeństwo

100/ 100Klasa: dobry
Format25 / 25
Frontmatter z nazwą i opisem, poprawna nazwa, opis do 1024 znaków, nazwa zgodna z folderem.
Odkrywalność25 / 25
Opis mówi, kiedy użyć skilla, ma sensowną długość i jest w 3. osobie.
Treść35 / 35
Co najmniej 150 słów i do 500 linii, nagłówki, listy kroków, przykłady albo kod.
Higiena15 / 15
Bez zaślepek typu TODO, bez ścieżek Windows, z licencją.
Ryzykobrak sygnałów w skanie
Pliki w paczce
1
Skrypty
0
Komentarze HTML
1
Adresy URL w SKILL.md
1
Przestarzałość

Brak sygnałów. Repozytorium zmienione 25.10.2026, bez odwołań do wycofanych modeli i API.

Licencja

MIT, otwarta: można używać i zmieniać, z zachowaniem informacji o autorze.

Co sprawdzić przed instalacją
  • SKILL.md zawiera komentarze HTML (1). Nie widać ich w podglądzie Markdown, a model je czyta.

Co robi i kiedy

Ocenia widoczność strony w wyszukiwaniu AI (GEO/AEO): możliwość wyciągnięcia odpowiedzi, gęstość faktów, dostęp crawlerów AI i encje, z wynikiem AI Visibility, tylko do odczytu.

Wyzwalacze z opisu

will AI engines cite this?

Argumenty

/geo <url|path> [--pages N] [--render static|auto|js] [--feed <path>] [--probe \"<question>\"] [--gsc-ai-export <csv>]
Oryginalny opis (EN)

Analyze and score only a page's AI-search visibility (GEO/AEO) — answer extractability, fact density, AI-crawler access and Google AI-feature snippet eligibility, entity linking, AI discovery files, and agent-readiness — and report an AI Visibility score with a citability breakdown, plus optional unscored probes (web-search presence, Search Console generative-AI impressions). Read-only. Use for "will AI engines cite this?", GEO/AEO, or ChatGPT/Perplexity/Google AI Overviews/Gemini optimization.

Jak działa

  1. What to do
  2. --probe "<question>" — web-search presence (repeatable)
  3. --gsc-ai-export <csv> — Search Console generative-AI import
Sekcje z nagłówków SKILL.md, w oryginale · 47 linii, 858 słów
Podgląd SKILL.md
---
name: geo
description: Analyze and score only a page's AI-search visibility (GEO/AEO) — answer extractability, fact density, AI-crawler access and Google AI-feature snippet eligibility, entity linking, AI discovery files, and agent-readiness — and report an AI Visibility score with a citability breakdown, plus optional unscored probes (web-search presence, Search Console generative-AI impressions). Read-only. Use for "will AI engines cite this?", GEO/AEO, or ChatGPT/Perplexity/Google AI Overviews/Gemini optimization.
argument-hint: "<url|path> [--pages N] [--render static|auto|js] [--feed <path>] [--probe \"<question>\"] [--gsc-ai-export <csv>]"
allowed-tools: Read, Grep, Glob, WebFetch, WebSearch, Bash, Agent
---
<!-- Portions Copyright (c) 2026 Enrique Rocha (@soyenriquerocha) - see LICENSE for original authors · tododeia.com · id er-d03758e1 -->

# /claude-seo-ai:geo

The AI-search (GEO/AEO) subset of the audit. **Read-only.**

`$ARGUMENTS` = `<url|path> [flags]`. `--pages N`, `--render static|auto|js` (default `static`) and `--feed <path>` (the Agentic Commerce Protocol product feed; it only does anything when the e-commerce vertical is active, and without it `M18.agentic.acp_feed_errors` stays `needs_api` — an unread feed is never a clean feed) are forwarded to the orchestrator and reach `audit.mjs` unchanged. `--probe` and `--gsc-ai-export` are handled here, not by `audit.mjs`: they are **probes — reported, never scored** (severity 0, excluded from the AI Visibility score and from every cap).

## What to do
1. Invoke **seo-orchestrator** with the target and flags and the instruction "AI path only": it acquires the snapshot with the scripts (never WebFetch), runs the deterministic checks, and dispatches **ai-search-geo-specialist** with **M6** (seo-entity-linking), **M11** (seo-geo-answerblocks), **M12** (seo-geo-factdensity), **M14** (seo-ai-crawlers — access + Google AI-feature eligibility), **M21** (seo-ai-discovery — llms.txt, agents.md, UCP, agentic sitemap), **M22** (seo-agent-readiness); plus **M5** (seo-schema-jsonld, via schema-generator) and **M4** (seo-rendering, via technical-auditor) because they feed AI visibility.
2. Run the probe flows below **only** when their flag is present.
3. Present from `report.json`: the **AI Visibility** score (band + interpretation), the citability breakdown by category, `needs_api` / `manual_review` counts, the prioritized GEO/AEO actions, any `probes` section (clearly separated from the score), and the `report.md` path.
4. Lead with the one thing Google documents: a page reaches AI Overviews / AI Mode by being **indexed and snippet-eligible** in Search (M14 `ai_eligibility`). Remind the user that **M21 — llms.txt and the other discovery files — is reported at weight 0** (Google Search ignores llms.txt; vendor support is partial). Never write files; offer `/claude-seo-ai:fix` for the safe AUTO fixes (e.g. the AI-crawler robots.txt preset).

## `--probe "<question>"` — web-search presence (repeatable)
A rough proxy for "does this site show up when someone asks this?", built from one search engine at one moment. It is **not** citation data.
1. For each `--probe` question, call **WebSearch** with the question verbatim. Do not rewrite it, do not add the brand name, and do not run extra queries the user did not ask for.
2. Read the organic results in order and build one JSON object — `rank` is the 1-based position in that result list, `url` and `title` are copied verbatim, and `host` is the audited site's hostname:
   ```json
   { "host": "example.com",
     "queries": [ { "query": "best sustainable running shoes",
                    "results": [ { "rank": 1, "url": "https://…", "title": "…" } ] } ] }
   ```
3. Pipe it to the reporter over stdin (nothing is written to the user's project); `--out` saves the probe inside the run directory, which is where `report.mjs` picks it up as `probes.web_search`:
   ```bash
   node "${CLAUDE_PLUGIN_ROOT}/scripts/probe-report.mjs" --host <host> \
     --out "<run_dir>/probes/web-search.json" [--history <dir>] <<'JSON'
   { "host": "…", "queries": [ … ] }
   JSON
   ```
   `--results <file.json>` reads the same JSON from a file instead of stdin.
4. It returns presence rate (queries where the host appears), best rank, the competitor-host tally, and a trend against earlier probe runs stored for that host. Report it under **`probes.web_search`** and quote its `disclaimer` field verbatim — echo the string the script emits (`DISCLAIMER` in `scripts/probe-report.mjs`, also written into `report.json` and `report.md`), never a paraphrase of it, so the model's prose and the machine-generated line beside it cannot disagree. Today that string reads: *"Web-search presence for these questions. This is NOT AI Overview, AI Mode, ChatGPT, or Perplexity citation data — no vendor exposes that. Indexing/retrievability is a documented precondition for Google AI features; presence here is necessary, not sufficient."*
5. The finding is `M14.probe.web_presence`, **severity 0**, method `web_search_probe`. Never let a probe change the AI Visibility score, and never describe a rank as a ranking measurement — WebSearch results are personalized, localized, and volatile.

## `--gsc-ai-export <csv>` — Search Console generative-AI import
1. The user exports the **Generative AI** performance report from Search Console by hand; there is no API for it. Pass the file:
   ```bash
   node "${CLAUDE_PLUGIN_ROOT}/scripts/gsc-ai-import.mjs" --csv <file.csv> [--host <host>] [--history <dir>] \
     > "<run_dir>/probes/gsc-generative-ai.json"
   ```
   The script prints the import and writes nothing itself, so redirect it into the run's `probes/` directory — that is what makes `report.mjs` report it under `probes.gsc_generative_ai` at data tier 2.
2. English and Spanish column headers are both recognized. The report carries **impressions only** — no clicks, no citations, no per-answer attribution — so the import reports impressions and nothing more.
3. Report it under **`probes.gsc_generative_ai`**. Findings, all **severity 0**: `M14.gsc_ai.impressions_present` (the export shows generative-AI impressions for this property), `M14.gsc_ai.zero_impressions` (the export parsed but contains none), `M14.gsc_ai.unavailable` (`needs_api` — no export supplied, or the file could not be parsed; the default state).
4. Say plainly what the number is not: impressions in Google's generative-AI surfaces are not citations, not clicks, and not a score input.

Both probe sections live beside the score, never inside it. If the user asks "did my AI visibility go up?", the honest answer is that these are proxies and the score is a structural assessment — the two are reported separately for exactly that reason. Respond in the user's language (EN/ES).

Wersje

RepozytoriumWynikLicencja
Ta strona · Hainrixz/claude-seo-ai100MIT
iamwaqargulzar/Marketing-Agent-OS100Apache-2.0
mangowhoiscloud/geode100Apache-2.0
techhorizonlabs/thl-open100MIT
TheSmokeDev/geo-skills100MIT
iamwaqargulzar/Marketing-Agent-OS90Apache-2.0

Migawka bazy z 28.10.2026 · wersja paczki 8f6d571525fd (skrót SHA-256 całej paczki)

Pobrania w ostatnich 30 dniach: 0 · ranking

Zgłoś problem z tym skillem: szkodliwa treść, błędny opis albo prośba autora o usunięcie.

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Uwagi i zgłoszenia

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