psychologist

Solid

Applied psychology discipline for product, organisational, and research contexts. Covers the full analytical lifecycle: cognitive-bias diagnosis, behavioural experiment design, individual-differences modelling, group dynamics analysis, replication-crisis literacy, and ethical research conduct. Grounds every inference in evidence hierarchy (case study through meta-analysis) rather than pop-psychology shorthand. Distinct from `core/product-conversion-readiness` behavioural-nudge augmentation — this skill applies academic discipline to product decisions, not conversion optimisation tactics. Use when: diagnosing decision quality across a team or product flow; designing or reviewing a behavioural experiment; evaluating published research before adopting its claims in product or policy; auditing a research protocol for ethical compliance; modelling variance across user segments; or stress-testing an organisational culture hypothesis.

AI & Automation 3 stars 0 forks Updated today MIT

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Skill Content

# Psychologist ## Cardinal Rule An effect with effect-size below 0.2 and N below 100 is a hypothesis at best; treating it as fact has misled half the field. No product decision, policy change, or research claim may cite a single unreplicated study as settled evidence. Every psychological inference requires an explicit evidence-tier label (see Evidence Hierarchy below) and a stated effect size. Claims that lack both are returned for revision before entering any decision record. ## Fail-Fast Rule Stop and return a structured failure when any of the following is true: - The research being cited is a single-study finding with no replication attempt and no pre-registration — label it hypothesis, not fact. - Sample characteristics are undisclosed or materially non-representative of the target population (WEIRD bias: Western, Educated, Industrialised, Rich, Democratic). - Causal language ("causes", "drives", "leads to") appears in a context that only warrants correlational language. - A behavioural experiment has launched without a pre-registered power analysis documenting the required sample size before data collection. - Personally identifiable psychological data is being processed without a documented legal basis under LGPD Art. 11 or GDPR Art. 9 (sensitive data category). Never approximate effect sizes from memory. Never infer population parameters from a convenience sample without stating the limitation explicitly. ## When to Apply Apply this skill when: ...

Details

Author
Canhada-Labs
Repository
Canhada-Labs/ceo-orchestration
Created
4 weeks ago
Last Updated
today
Language
Python
License
MIT

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