
Persona Content Quality System
SkillSkill
Evidence-tiered brief template that blocks unverified health claims before they reach the LLM. Upstream prevention, not downstream fact-checking.
About
A brief template system that prevents AI from publishing unverified health and wellness claims. Every claim in a content brief requires an evidence tier and a source before it reaches the language model. If you cannot assign an evidence tier, the claim does not go in the brief.
The evidence tier system has six levels. T1 is strong RCT evidence or meta-analysis: state as fact. T2 is good replicated RCTs: 'Studies have found...' T3 is observational: 'Research suggests...' T4 is animal or in vitro studies: qualifier required. T5 is traditional use only: qualifier required. Claims without a tier are blocked at the brief stage.
Also includes a Claude Code post-creation verification prompt that checks each claim in the finished article against its brief-stage evidence tier and flags mismatches.
Validated against 20 live articles on a wellness site: caught a Van Dongen sleep deprivation misquote (stated 24-hour cognitive equivalence, correct is 48 hours), a CBT-I remission rate inflation (stated 75-80%, actual around 60-65%), and three supplement efficacy claims stated without required qualifiers.
What is included: the full brief template with tier and source fields, the six-tier classification guide with required wording per tier, the Claude Code post-creation verification prompt, and a list of the five most common LLM health content errors.
Best for anyone running AI-generated health, wellness, or nutrition content who needs to maintain factual accuracy at scale.
Core Capabilities
- 6-tier evidence classification system with per-tier article wording requirements
- Brief template with mandatory tier + source fields for every health claim
- CC post-creation verification prompt block — catches errors before publishing
- The 5 most common LLM health content errors: examples and correction patterns
- Validated against 20 live articles: Van Dongen misquote, CBT-I inflation, supplement overclaims
- Adaptable to any health/wellness/nutrition content operation
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Version History
This skill is actively maintained.
March 25, 2026
One-time purchase
$29
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Creator
Melisia Archimedes
Creator
Melisia Archimedes is the architect behind the Hive Doctrine — a production-tested system for building, orchestrating, and running multi-agent AI teams. I've spent years in the field, not on the whiteboard. Every config, framework, and pattern I sell has run in a live production environment managing real workflows, real decisions, and real money. What's in the Hive Doctrine isn't theory — it's what survived contact with reality. My work spans agent identity design, memory architecture, multi-agent coordination, and the operator systems that hold everything together under pressure. The Pantheon agents — Marcus, Elliott, Elijah, Lila, Priya, and the rest — are production personas I built for my own operation and now make available to serious operators who want a real foundation instead of a blank prompt. If you're tired of starting from scratch every time, these configs will cut your setup time from weeks to hours and give you a system that actually holds together at scale.
View creator profile →Details
- Type
- Skill
- Category
- Content
- Price
- $29
- Version
- 1
- License
- One-time purchase
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