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From Auto-PsyNet
FORMULATE step — choose the experimental paradigm and design. Maps the question archetype to a PsyNet paradigm via config/affinity.yaml, reads the recipe + domain priors, may propose elevating to a differentiating paradigm, and specifies conditions, counterbalancing, prescreens, population/languages, and consent.
How this skill is triggered — by the user, by Claude, or both
Slash command
/apsy:designThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
> EXECUTION CONTRACT. Apply the **methodologist** persona. Writes §4 of `.apsy/research-plan.md`. This is
EXECUTION CONTRACT. Apply the methodologist persona. Writes §4 of
.apsy/research-plan.md. This is where the plugin's proactive design intelligence lives.
Read .apsy/research-plan.md §1–§3 and the named archetype + domain.
Query config/affinity.yaml: the archetype yields candidate paradigms (a soft prior). Read the
matching skills/psynet/psynet-function/<p>.md recipe(s) and the config/domains/<domain>.md priors.
Present the canonical paradigm match AND, when defensible, a novel cross-over with its trade-off
(e.g. "a one-shot rating works, but a cross-cultural GSP would recover the whole representation — more
powerful and more novel"). Use AskUserQuestion; the user chooses. Never silently lock a paradigm.
For the chosen paradigm, specify: conditions; within vs between; counterbalancing + randomization;
prescreening (PsyNet modules, e.g. HeadphoneTest, AttentionTest) + exclusion criteria;
target population + languages (cross-cultural scoping — flag measurement invariance if comparing
groups); and consent (default MainConsent; note apsy:consent for a custom form).
Write §4 (Design). Set bin/apsy-state.sh set paradigm "<paradigm>".
Validation gate: §4 complete; the chosen paradigm matches a known skills/psynet/psynet-function/ recipe;
population + languages stated.
npx claudepluginhub haoyu-hu/auto-psynet --plugin apsyGuides creation, editing, and verification of skills for AI coding agents using test-driven development with subagent scenarios. Use when authoring or debugging skills.