Use when targeting The Lancet Public Health or deciding whether a population-health study fits this venue. Encodes the journal's fit, the population-level intervention, epidemiology, and policy evidence bar, reporting-guideline and registration requirements, Lancet specialty house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.
SkillScore73Maintained
Automatic
◆Writing & Editing pack
Last verified 9/1/2026
What it changes
Passed 16 of 22 test cases with the skill, and 15 of 22 without it.
Without skill68%
With skill73%
Checks it passed that the model alone missed
Rates the fit level as Low.
Re-routes the manuscript to `jama-oncology`.
Emphasizes the requirement for transparent population denominators.
and 2 more in the full report
4 fixed12 passed either way3 still failing3 broke
Pass-rate lift
+5 pp
Tokens
+22%
Agent turns
0%
Response time
-34%
Model gemini-3.6-flashMeasured 9/1/2026v116 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 4
Prompt
Our study evaluates 5-year progression-free survival in 400 stage III colon cancer patients undergoing adjuvant immunochemotherapy at three tertiary hospitals. The study team is considering The Lancet Public Health. Please evaluate fit using structured review fields and suggest a better-matched venue.
What was checked, without and with the skill
Checked
Without skill
With skill
Rates the fit level as Low.
Missed
Passed
Re-routes the manuscript to `jama-oncology`.
Missed
Passed
Identifies individual clinical oncology patient outcomes as the main rejection trigger.
Passed
Passed
case-08 · gemini-3.6-flash · 9/1/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md127 linessingle file
The Lancet Public Health (the-lancet-public-health)
Journal positioning
The Lancet Public Health is a Lancet specialty journal for population and public-health
research — population-level interventions, health policy and systems, epidemiology and
disease burden, and global-health and health-equity research with population-level
relevance. It favors rigorous studies whose unit of interest and consequence is the
population, not the individual patient: large-scale epidemiology, policy and natural
experiments, modelling with clear public-health decision value, and interventions
addressing inequalities or the social determinants of health. The defining misfit is an
individual-level clinical study (a drug or device effect in patients) with no
population, policy, or equity dimension — that belongs in a clinical journal. This skill
is a fit / venue-selection / re-framing aid; it is not clinical or regulatory advice
and does not replace the journal's current instructions for authors. Before submitting,
re-check the live The Lancet Public Health author instructions.
When to trigger
The author names The Lancet Public Health for a population-health, epidemiology, or
policy study and wants a fit/framing check.
A study must be re-framed around a population-level intervention, burden, or policy
question with equity relevance.
The author is choosing between The Lancet Public Health, a clinical specialty journal,
and general medicine.
The author needs the journal's reporting-guideline, registration, and desk-reject
expectations for population/policy evidence.
Scope & topic fit
Population-level interventions and policy/natural experiments (taxation, regulation,
screening programmes, vaccination, public-health service delivery).
Epidemiology, disease-burden, surveillance, and risk-factor studies at population
scale, including global and comparative analyses.
Health-systems, health-services, and health-economics research with population-level
decision relevance.
Health-equity, social-determinants, and inequalities research with population-level
framing and policy implication.
Modelling and forecasting studies (transmission, burden, intervention impact) with
transparent assumptions and public-health decision value.