Pharmaceutical GEO High-Citation Content Creation
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About this skill
Problem
Creating high-citation pharmaceutical GEO content is not just copywriting. The workflow must verify the Python runtime and authorization state before using protected instructions, otherwise output may bypass platform rules or rely on stale context.
Workflow
It begins with a silent Python environment check to resolve PYTHON_CMD and avoid Windows cases where python opens the Microsoft Store. Then it runs scripts/auth.py for local credential cache, user binding, and remote validation. Signals such as AUTH_REQUIRED or CREDENTIALS_MISSING trigger an automatic binding flow. Only a failed recheck after binding stops execution and reports the error. After AUTH_OK, it calls scripts/protected.py to retrieve protected instructions and follows them for content creation.
Boundaries
It depends on the Baitong AI authorization chain and is not suitable for offline generation or environments without WorkBuddy binding. Output is tied to protected instructions and should not be completed from history alone; business inference must stop if authorization fails.
Use Cases
- Generate protected pharma GEO content after auth.
- Fix Python path before running auth scripts.
- Auto-bind WorkBuddy JWT when credentials missing.
- Report auth, network, and permission failures.
Best For
- Pharma GEO content engineers producing gated articles.
- Baitong AI skill maintainers handling auth signals.
- WorkBuddy integration engineers wiring JWT binding.
- Pharma editors verifying protected-instruction output.
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