One line per decision you make: what, why, and which alternative you rejected — takes only 30 seconds.

Do not say "I know how you feel". Name the feeling with a precise word and verify it.

Pick 3 emotions on a Plutchik wheel (level 2) you feel now — precise labeling = calm.

In suffering, apply Neff's 3 steps: acknowledge, common humanity, self-kindness.

Trigger event → thought → distortion → counter-evidence → reframe.

Replace "you seem upset" with wheel-precise: "you seem frustrated because...".

Log mood (1-10) AM, noon, PM with a one-word cause — discover your patterns.

In anger, dissect: Antecedent → Belief → Consequence.

When entering a room or call, note your mood before and after to see what you "caught".

When someone near you is distressed, lower your own voice and pace first — your calm body lends calm.

When you reflexively say "I'm fine", pause and ask your body 3 questions before accepting the default answer.

Count how many times you "performed" a smile or enthusiasm you didn't actually feel at work today.

When your mood dips mid-social-day, apply a 90-second intervention before it spoils your interactions.

After guessing what a close person feels, verify explicitly instead of trusting your hunch alone.

Log every task you do for a full week, then tag: delegable / non-delegable.

Each significant decision: a text file with context, options, choice, consequences.

Each major decision: context, options, decision, consequences — one page, sequential.

Ask the model to decompose the problem and show its reasoning before answering, raising accuracy on complex tasks.

Add "think step-by-step inside <thinking> tags before answering" — boosts complex-problem accuracy 30-40%.

Ask the model to "think out loud" step by step before the final answer, especially for logic and math problems.