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SEO Indexing Playbook

This repository is prepared for discoverability, but search engines index public pages only after the repo is pushed, GitHub Pages is enabled, and crawlers revisit the site. This document gives the exact public-facing checklist.

Primary search phrases

Use these phrases consistently in README, repository description, GitHub topics, release notes, and the GitHub Pages landing page:

  • local AI model builder
  • governed LLM builder
  • GGUF model training pipeline
  • local-first AI governance
  • benchmarked local language model
  • model promotion gate
  • regression-safe LLM training
  • AI model provenance
  • reproducible AI training receipts
  • ARC-Neuron LLMBuilder
  • Omnibinary AI memory
  • Arc-RAR model archive
  • local AI cognition lab
  • sovereign AI model builder
  • offline LLM builder

GitHub repository settings

Recommended repository description:

Governed local AI cognition lab for building, benchmarking, and promoting GGUF-oriented model candidates with receipts, rollback, provenance, and regression-safe gates.

Recommended topics:

gguf local-ai llm-builder governed-ai model-governance ai-provenance ai-receipts offline-ai sovereign-ai benchmark llm-evaluation regression-testing model-promotion machine-learning python pytorch llama-cpp agentic-ai knowledge-preservation reproducible-ai

GitHub Pages

Enable GitHub Pages from the main branch. The repo already contains:

  • _config.yml
  • index.md
  • robots.txt
  • sitemap.xml support through jekyll-sitemap
  • JSON-LD metadata in docs/seo_metadata.jsonld

Release SEO checklist

For each release:

  1. Use the release title format: ARC-Neuron LLMBuilder vX — Governed Local AI / GGUF Candidate Pipeline.
  2. Include the honest status line first.
  3. Include benchmark counts and incumbent status.
  4. Include five use-case bullets.
  5. Link README, PROOF, QUICKSTART, and production handoff docs.
  6. Add a changelog section with exact changed files.

External indexing checklist

After pushing:

  1. Submit the GitHub Pages URL to Google Search Console.
  2. Submit the GitHub Pages URL to Bing Webmaster Tools.
  3. Add the repo to the TizWildin / GareBear99 hub site.
  4. Link it from ARC-Core, Arc-RAR, Omnibinary, Cleanroom Runtime, and arc-language-module READMEs.
  5. Create a short demo video or post titled around local AI model builder with rollback receipts.
  6. Post release notes on GitHub Discussions.

What not to claim

Do not claim:

  • Claude-level capability,
  • Gemma-scale trained checkpoint,
  • medical/therapy-grade safety,
  • guaranteed autonomous learning,
  • or production frontier model status.

Correct wording:

production-candidate governance loop for local model growth, benchmarked candidates, provenance, and rollback-safe promotion.

Sponsor Platform SEO Targets

Sponsor-related indexing phrases to use naturally in README, releases, and posts:

  • local-first AI infrastructure sponsor
  • CPU-first GGUF runtime testing
  • benchmark receipts for local AI models
  • sponsor-backed custom repository templates
  • local AI model lifecycle platform
  • deterministic local AI governance
  • rollback lineage for AI model promotion

Primary support URL:

https://github.com/sponsors/GareBear99

Keep sponsor language factual. Do not imply guaranteed AGI, guaranteed revenue, or unlimited custom software delivery.