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Super seo growth

Skill arpitexplores/super-seo-growth

Portable Markdown skill for AI vibe coding with SEO growth: AI SEO, GEO, LLM visibility, content optimisation, programmatic SEO, and citation-ready organic growth.

Install
npx -y skills add arpitexplores/super-seo-growth

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

SEO growth: content optimisation, programmatic SEO, AI/GEO visibility, and ongoing performance improvements. Use after a baseline audit or run a quick check first.

SKILL.md

2.0 KB, 413 tokens by cl100k_base, as published. Nobody here has run it

Super SEO Growth

Overview

Drive organic growth through content quality, programmatic expansion, and AI search visibility.

User Intent Examples

  • "Need help with SEO Content for my product/site."
  • "Create a plan for AI/GEO Visibility."
  • "Audit or improve Programmatic SEO."

Capabilities

  • Content refresh, topical authority, and keyword coverage
  • Programmatic SEO templates and scalable page strategies
  • AI/GEO visibility, citation optimisation, crawler policy, and fan-out coverage
  • Iteration plan with measurement and cadence

Routing Map (Modules)

  • SEO Content -> references/modules/seo-content.md
  • AI/GEO Visibility -> references/modules/seo-geo.md
  • Programmatic SEO -> references/modules/seo-programmatic.md

Default Flow

  1. If no recent audit or baseline is unknown, ask for the URL and last audit date.
  2. If the request targets AI/GEO or LLM visibility, jump to the GEO module.
  3. If the request targets scale via templates, jump to the programmatic module.
  4. Otherwise, start with the content module.

Minimal Intake Questions

Ask only what is missing:

  • Primary URL(s)
  • Target market/region
  • Primary goal (traffic, leads, signups)
  • Content scope (blog, landing pages, docs)

Output Format

  • Growth priorities with rationale
  • Execution plan (content, programmatic, GEO)
  • Measurement plan and cadence
  • Risks and dependencies

Bundled References

  • references/modules/
  • scripts/
  • assets/
  • agents/

Compatibility Notes

  • If any module references slash commands or tool-specific paths, translate them into plain-language steps.
  • Keep outputs platform-agnostic unless the user specifies a specific tool, stack, or agent.

Guardrails

  • Do not invent search data or rankings.
  • Tie every action to measurable outcomes.
  • Keep recommendations implementable.

Gives 0 of the 12 instructions most performance cost skills give in 413 tokens

Counted across 803 of the 1,058 authors here whose files we hold, read 2026-08-07

  • keep skill files under 500 linesin 82 of 803, across 16 files
  • use imperative form in instructionsin 80 of 803, across 9 files
  • draft assertions while test runs are in progressin 75 of 803, across 9 files
  • create two to three realistic test promptsin 74 of 803, across 9 files
  • write skill descriptions to be pushyin 72 of 803, across 7 files
  • save test cases to evals jsonin 72 of 803, across 6 files
  • ask questions about edge cases and input formatsin 72 of 803, across 7 files
  • save timing data immediately when runs completein 70 of 803, across 5 files
  • include all trigger conditions in the skill descriptionin 69 of 803, across 3 files
  • launch all test runs in a single turnin 69 of 803, across 3 files
  • capture intent before writing a skillin 67 of 803, across 1 file
  • import directly instead of barrel filesin 52 of 803, across 15 files

Said here and by no other author read

  • ask for URL and last audit date if unknown
  • jump to GEO module for AI/LLM visibility requests
  • jump to programmatic module for template scaling requests
  • start with content module by default
  • ask only missing intake questions
  • translate tool-specific paths into plain-language steps

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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