Atlas — GEO / Agentic Commerce Pack

What it does

Atlas makes merchant sites machine-readable for LLM/agent discovery. Generates /llms.txt, agents.md, and product-feed hygiene packs so purchasing agents can find and trust merchant catalogs — without promising volatile citation ranks.

Why it matters

AI-referred traffic is the next wave. ChatGPT, Claude, Gemini, Perplexity — they all crawl /llms.txt + agents.md to decide which merchants to surface. Without those files, your storefront is invisible to AI agents.

How it works

1. Audit current storefront (llms.txt, agents.md, schema.org coverage, product feed)
2. Generate /llms.txt + agents.md + sitemap_agentic_discovery.xml
3. Verify with the included scorecard (AI referral sessions, citation sample set, feed error count, schema coverage %)
4. PR to storefront repo, re-crawl, ship
5. Pair with Skyler/Lex as separate SKUs (Atlas feeds GEO only)

What ships

• SKILL.md — installable OpenClaw skill playbook
• SOUL.md — Atlas identity + standards-first tone
• FIELD_GUIDE.md — llms.txt skeleton + scorecard + install steps
• AGENTS.md — daily GEO ops SOP
• logo_master.png — brand logo (2048×2048)
• logo_stamp.png — corner overlay (1024×1024)

Proven

• Built for merchants and agencies chasing AI-referred traffic without enterprise GEO retainers
• Standards-first: llms.txt + agents.md + schema.org JSON-LD
• No volatile citation promises — just file generation + verification
• Pair cleanly with Skyler (recruiter) and Lex (legal)

Stack

• Persona: Atlas (Generative Engine Optimization specialist)
• Engine: OpenClaw agent runtime
• Output: llms.txt, agents.md, schema.org, sitemap.xml
• Price: $49

Compliance

• Standards-first (llms.txt, agents.md, schema.org)
• No citation-rank promises
• Scorecard-based ROI measurement