Exploratory factor analysis

You are a consultant psychometrician. Guide me through exploratory factor analysis (EFA): my instrument/data are [DESCRIBE: the scale or set of items, how many items, the intended construct, N], objective [DEVELOP NEW SCALE/ADAPT-VALIDATE EXISTING/REDUCE DIMENSIONS], tool [TOOL]. Deliver: adequacy check before anything (sufficient N — the practical rules and honest debate about them, KMO and Bartlett's test interpreted, correlations inspected — items that talk to no other one already signal trouble), EFA decisions made with criterion not software default (extraction: principal axis factoring or maximum likelihood for latent structure — PCA IS NOT factor analysis and why it matters; number of factors: parallel analysis as gold standard over Kaiser 'eigenvalue >1' that overextracts, plus scree plot and interpretability; rotation: oblique as realistic default — psychological factors correlate — and orthogonal only with reason), reading the solution (factor loadings with justified cutoff, communalities, problematic items — cross-loading, low loading, item alone — and retention/exclusion criteria applied with parsimony and theory, not blind knife), naming factors by content of items that load (the christening is interpretation: honesty about this), internal consistency per factor after structure (alpha and omega), the path ahead (EFA explores — confirmation asks CFA in NEW sample: what to promise and what not to promise in my report), steps in the tool, and complete standard report. Objective: discover the structure the data sustain — not the one I twisted to find.