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View on GitHub → SEO and GEO review for one article, in one command. Give the skill a Markdown draft or a published URL. It measures the target keyword, pulls the live Google SERP and AI Mode answer, parses top-ranking competitor pages, queries AI answer engines to see what they return and whom they cite, runs deterministic on-page checks, and returns a scored Markdown report plus a JSON evidence file.

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Install

After installing, start a new agent session so the skill loads.

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What can agents do with it?

Pre-publish review

“Review draft.md for SEO and tell me whether AI Overviews would cite it.”

Published URL audit

“Run an SEO + GEO review on https://example.com/blog/post and show me the scorecard.”

Content gaps

“Compare my article with the pages ranking for ‘generative engine optimization’ and list what they cover that I don’t.”

AI citation checks

“Give me the top rewrite suggestions to make this post citable by ChatGPT and Perplexity.”

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Requirements

  • Python 3.9 or later (standard library only)
  • If the variable is not set, the script also reads AISA_API_KEY=... from ~/.aisa/credentials.

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Compatibility

Works with any agentskills.io-compatible harness, including Claude Code, Claude, OpenAI Codex, Cursor, Gemini CLI, OpenCode, Goose, OpenClaw, Hermes, and other runtimes that support skill folders.

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Quick start

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Spend approval

The data calls are billed to your AIsa balance, so the skill never runs paid stages before you approve them:
  1. review <source> --dry-run prints every planned call with a nominal and a documented maximum total.
  2. You approve that scope.
  3. The agent re-runs the command with --yes. Without --yes, the script prints the plan and exits with code 2. --max-usd rejects any plan whose documented maximum exceeds it.
The report’s Spend section lists every call with its reported cost. --cache-dir stores raw responses so re-runs and re-renders are free.

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Pipeline

Keyword → SERP → Competitors → Content gap → SEO audit → GEO audit → Rewrite suggestions → Scorecard The report scores SEO and GEO each from 0 to 100, averages them, and assigns a grade from A to F. A failed engine is reported as a data gap, not as “not cited”.

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Commands

Shared flags: --keyword, --site-domain, --location-code (default 2840, United States), --language-code (default en), --database (Semrush, default us), --geo-location, --top, --engines, --fast, --deep, --model (or AISA_REVIEW_MODEL), --no-llm, --cache-dir, --out, --json-out. review adds --dry-run, --yes, and --max-usd.

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When to use

  • “Review this article for SEO before we publish.”
  • “Will AI Overviews or ChatGPT cite this post? What do I change?”
  • “Run a GEO audit on this URL.”
  • “Give me an SEO + GEO scorecard and rewrite suggestions.”
Do not use this skill for keyword research from scratch (use SEO Keyword Research), full technical site audits, backlink audits, or writing the article. For a draft, pass --site-domain so internal links and “is my domain cited” can be evaluated before publishing.

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Get started

  1. Sign up at aisa.one and create an API key in the console.
  2. Set it in your shell: export AISA_API_KEY="your-key".
  3. Install the skill with one of the commands under Install, then start a new agent session.

SEO Keyword Research

Build a keyword strategy before you write.

DataForSEO keyword overview

Volume, difficulty, intent, and CPC endpoint.

Semrush keyword overview

Cross-check keyword metrics.