StackTerminal.Health

BETA

Safety & Disclaimer

StackTerminal.Health is an educational platform. Nothing on this site constitutes medical advice, diagnosis, or treatment. Always consult a qualified healthcare professional before starting, stopping, or changing any supplement, drug, or health protocol.


How our recommendations work

Stack outputs are generated from your profile (goals, constraints, body metrics), plus optional wearable and bloodwork context, then mapped against our ingredient library & evidence records. Outputs are personalized & evidence-linked, but still probabilistic & should be treated as decision support.

  • • Free plan includes 1 stack & 1 stack update/regeneration.
  • • Pro includes unlimited stacks & unlimited stack updates/regenerations.
  • • AI Risk Assessment & Reel Check are additional layers, not medical diagnosis.

How we classify ingredients

Each ingredient is classified as either:

Supplement

Mainstream, widely available over-the-counter ingredients that have been sold as dietary supplements for years, such as creatine, magnesium, omega-3s, ashwagandha, or vitamin B12. Evidence quality still varies & we display the evidence grade on every entry.

Research compound

Compounds primarily studied in laboratory or clinical research settings. They may be subject to regulatory restrictions, limited human-safety data, or ongoing review by bodies such as the FDA or EFSA. Examples include NMN (which the FDA has raised exclusion concerns about as a dietary supplement), or ingredients with only animal-model data. These entries are provided for informational purposes only. We do not recommend sourcing or using them without medical supervision.


Evidence quality & source veracity

We display evidence grades & study context on ingredient pages & stack detail views. We also run interaction checks (including timing & pharmacokinetic conflicts) & attach source links where applicable.

  • • Evidence strength varies by outcome, dose, population, & study design.
  • • Not every stack claim has equal certainty; we explicitly surface uncertainty in stack output.
  • • Citations & interaction links are periodically reviewed & corrected when needed.
  • • If you spot a mismatch, report it & we will review & patch quickly.

AI-generated features

AI is used in stack naming/description refinement, risk commentary, Reel Check claim analysis, & some moderation workflows. AI outputs can be wrong, incomplete, or out of date. Use them as a starting point, not final authority.

  • • Reel Check verdicts support evidence review, not legal/clinical adjudication.
  • • AI Risk Assessment highlights practical risks, but is not medical clearance.
  • • Automated moderation may reject valid comments; you can revise & repost.

Community stacks & comments

Community stacks are user-generated protocols. StackTerminal does not review, endorse, or verify individual stack submissions. They are labelled Unvetted to reflect this. Treat them as starting points for your own research, not as recommendations.

Comments are moderated for abuse/spam/off-topic content. Rejections are returned with constructive guidance so users can improve & resubmit.


Data protection & privacy handling

Wearable & bloodwork data are used to personalize outputs & safety checks. We do not sell personal data & do not share it with ad networks for targeting.

  • • Supported integrations include Strava, WHOOP, Oura, Garmin, Fitbit, TrainingPeaks, & Apple Health summaries.
  • • Bloodwork PDFs are processed server-side; extracted text is scrubbed before AI processing.
  • • We store integration summaries needed for personalization & staleness detection.
  • • You can disconnect integrations, opt out of digest emails, or delete your account & related data.

Operational safeguards

  • • API-level tier enforcement for feature limits (not UI-only).
  • • Staleness markers when wearable archetypes drift from the stack snapshot used at generation.
  • • Structured pre-check & interaction checks to reduce obvious safety misses.
  • • Ongoing review cycles for evidence data quality, citation integrity, & moderation quality.