From epsl-skills
Designs sampling, analytical, experimental, or modeling programs for EPSL manuscripts to ensure process-level claims are defensible, with sample context, reference materials, replication, and model resolution planned before data exist.
How this skill is triggered — by the user, by Claude, or both
Slash command
/epsl-skills:epsl-study-designThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
EPSL reviewers reverse-engineer the design from the claim: if the paper says "this rate constrains
EPSL reviewers reverse-engineer the design from the claim: if the paper says "this rate constrains
mantle upwelling," they ask whether the samples, standards, and models could ever have shown
otherwise. The predictable failures are samples without context, analytical campaigns without
traceability to reference materials, models without resolution tests, and rates without an
independent time anchor. Design against them before the first analysis. Data reduction and
uncertainty reporting live in epsl-data-analysis.
| If you claim... | Design must include... | Reviewer's killer question |
|---|---|---|
| An age / a rate | community standards, blanks, procedural replicates, stated decay constants | "traceable to what, at what 2σ?" |
| A mantle/crust source signature | screening for alteration + a crustal-contamination test | "is this source or shallow overprint?" |
| Deep structure from an inversion | resolution/recovery tests, damping trade-off shown | "can your data even see that depth?" |
| A P–T history from experiments | demonstrated equilibrium (reversals/time series) | "did the runs equilibrate?" |
| A planetary-interior property | sensitivity to the unmeasured parameters (e.g., core size, mantle Fe) | "how much does the answer move?" |
To support "the eruption tempo, not total volume, drove the crisis," the design (illustrative) builds its defenses first:
The design's decisive move: precision requirements were derived from the hypothesis contrast, so the campaign was sized to answer the question rather than hoping the errors come out small.
【Design】field / analytical / experimental / modeling + target observable
【Context】sample metadata + screening plan
【Traceability】standards / blanks / decay constants (or model benchmarks)
【Replication】level + n
【Discrimination】which hypotheses predict different outcomes
【Time anchor】chronology + its uncertainty (if a rate)
【Next】epsl-data-analysis
../../resources/external_tools.md — analytical facilities' norms, geochronology tooling, model codes../../resources/official-source-map.md — EPSL scope and methods-transparency expectationsnpx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin epsl-skillsReduces isotope, geochronology, and geophysical data with full uncertainty budgets, MSWD, weighted means, Bayesian age models, and inversion diagnostics for EPSL manuscripts.
Guides design of manipulative experiments, observational studies, and process models for Global Change Biology manuscripts. Helps avoid pseudoreplication and match scale to claim.
Evaluates manuscript fit for Earth and Planetary Science Letters (EPSL) and provides quantitative process-science criteria, house-style guidance, and desk-reject heuristics.