How to use
- Copy the installation command and review the source package before installing it in your own agent environment.
- Check the source document for required tools, credentials and supported hosts.
- Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill plan-effect-sizeBefore you start
- Installation does not include a model subscription, API allowance or permission to access your files.
- Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document
Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.
plan-effect-size
Purpose
Choose effect-size estimands and conversion rules appropriate to outcomes and study design.
Input contract
yaml
required: [outcome_schema, study_designs, comparison_target]
optional: [reported_statistics, variance_rules, transformation_options]
constraints: [estimand, direction, and conversion assumptions must be explicit]Procedure
- Match each outcome and design to a valid estimand.
- Define direction, scale, variance, and required conversions.
- Record unavailable statistics and assumptions for any conversion.
- Produce a harmonized effect-size plan with incompatibilities.
If the effect measure and transformation rules are fixed, consider design-data-extraction as the next tactic.
Output contract
yaml
produces: [estimand_plan, conversion_rules, variance_requirements, incompatibility_log]
delta_fields: [decisions, assumption_updates, uncertainties, open_questions]Quality gates
- Effects are comparable only under declared assumptions.
- Conversions remain traceable to reported statistics.
Failure and counterexamples
Do not convert incompatible constructs into a common effect size merely to increase sample size.
Provenance map
resolved: effect-size-planning
