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geo-analysis

geo-analysis

github.com/openclaudiaMarketing & growth722125 installsUpdated 1w ago
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About geo-analysis

geo-analysis is a GEO/SEO analysis skill for marketing teams that produces domain reports on AI visibility, market research, and competitors. It uses the Enception API and can recalculate visibility after brand-name corrections.

Key features

  1. 01Analyze AI brand visibility
  2. 02Research markets and competitors
  3. 03Generate PDF reports
  4. 04Recalculate visibility after brand-name corrections

Use cases

  1. 01Assess brand recommendations in ChatGPT and Google AI
  2. 02Prepare domain analysis reports for clients
  3. 03Correct visibility results with brand aliases

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/openclaudia/openclaudia-skills --skill geo-analysis

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

Details

From the project README

GEO Analysis

Run a full GEO/SEO analysis for a domain and get a client-ready PDF report: AI visibility (is the brand recommended by ChatGPT / Google AI), deep market research, and competitor landscape.

Thin wrapper over the Enception client-analysis API. Three operations: start, status, report (plus an optional brand-name correction).

Disclosure: contributed by Enception AI and calls Enception's paid external API. Docs: https://www.enception.ai/doc/api-client-analysis

Requirements

  • ENCEPTION_ANALYSIS_API_KEY — sent as the x-api-key header. Self-serve: sign up at https://www.enception.ai, then generate a free-tier key under Account → API Key (2 analyses/month free; contact the team for higher limits). Rate limit: 10 requests/minute.

1. Start

POST https://www.enception.ai/api/external/client-analysis/start

Required: website_url, primary_region, core_goals. Sensible defaults: primary_region=us, core_goals=traffic, output_language=en, competitors=[]. The API normalizes URLs to a bare domain and rejects IPs. Returns { id, message } — save the id.

Pick output_language from an explicit request first, then the user's conversation language, then the domain TLD (.cn → zh; otherwise en).

curl -s -X POST "https://www.enception.ai/api/external/client-analysis/start" \
  -H "x-api-key: $ENCEPTION_ANALYSIS_API_KEY" -H "Content-Type: application/json" \
  -d '{"website_url":"https://example.com/","primary_region":"us","competitors":[],"core_goals":"traffic","output_language":"en"}'

Only override primary_region / core_goals / competitors if the user specifies. core_goals is free text (e.g. traffic, ranking). Competitors: [{"name":"X","domain":"x.com"}, ...] (max 5). For multiple domains, fire one POST each and collect the ids.

2. Status

POST https://www.enception.ai/api/external/client-analysis/status with body { "id": "<id>" } and the same x-api-key header. Returns { status: 'pending' | 'failed' | 'succeeded', progress_percent?, pdf_url? }.

A full run takes ~20–45 minutes — the bottleneck is the deep market-research step. Poll on a long interval (minutes, not seconds). succeeded ⇒ ready to fetch the report. If a run fails or stalls indefinitely, report that to the user rather than inventing results.

3. Report

GET https://www.enception.ai/api/external/client-analysis/report/<id> — public, no auth; shareable by id. Works once status is succeeded (also serves partial runs).

curl -s -o geo-analysis-example.pdf \
  "https://www.enception.ai/api/external/client-analysis/report/<id>"

Confirm it's a real PDF (file geo-analysis-example.pdf), then give the user the file and/or the public URL.

4. Fix "zero visibility" (brand-name correction)

POST https://www.enception.ai/api/external/client-analysis/update-brand with body { "id", "brand_name"?, "alternative_names": [...] } and the x-api-key header.

When a report shows zero/low AI visibility but the brand IS recommended by ChatGPT/Google, it's almost always because the brand is only known by its fused domain label (e.g. pudurobotics) while AI engines say "Pudu Robotics". Supply the real name + aliases and the route recomputes visibility from the already-stored answers (no re-query — fast), then re-fetch the report.

curl -s -X POST "https://www.enception.ai/api/external/client-analysis/update-brand" \
  -H "x-api-key: $ENCEPTION_ANALYSIS_API_KEY" -H "Content-Type: application/json" \
  -d '{"id":"<id>","brand_name":"Pudu Robotics","alternative_names":["Pudu","PuduBot"]}'

Returns { success, mention_rate, overall_score, average_position, analysis_regenerated }. New analyses resolve the brand name automatically; this is the manual correction path for existing reports.

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