cogpsych-theory-and-hypotheses
Use when stating the theory, formalizing the model, and deriving predictions for a Cognitive Psychology (Elsevier) manuscript. The journal rewards a formal/computational account whose parameters mean something and whose predictions discriminate it from rivals. Structures the theory and the model that the experiments test; it does not fit the model or run analyses.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cogpsych-theory-and-hypotheses --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Theory, Models & Hypotheses (cogpsych-theory-and-hypotheses) Cognitive Psychology rewards a **formal account of a cognitive process** — a computational or mathematical model whose parameters have interpretable meaning and whose predictions can be **fit to data and compared against rival models**. The cardinal move here is to turn a verbal theory into a model that makes the experiments *discriminating*, and to separate predicted (confirmatory) from discovered (exploratory) results. ## When to trigger - Specifying the theory and the formal/computational model that the experiments will test - Deriving the predictions that **separate** your account from rival models - Co-designing the model with the experiments (iterate with `cogpsych-study-design`) - A reviewer said the work is "atheoretical," "the model is just a curve fit," or "your data don't distinguish the accounts" ## Build the theory-and-model 1. **State the cognitive theory.** What mechanism or representation explains the phenomenon, and why — in words, before equations. Name the rival accounts you intend to adjudicate. 2. **Formalize it.** Write the model: its representations, processes, free parameters, and what each param
- When to trigger
- Build the theory-and-model
- Avoiding the "just a curve fit" objection
- Worked micro-example — theory to discriminating prediction (illustrative)
- Theory-stage reviewer pushback and the venue fix
- Theory calibration anchors
- Anti-patterns
- Output format
- Supplementary resources
What does the cogpsych-theory-and-hypotheses skill do?
Use when stating the theory, formalizing the model, and deriving predictions for a Cognitive Psychology (Elsevier) manuscript. The journal rewards a formal/computational account whose parameters mean something and whose predictions discriminate it from rivals. Structures the theory and the model that the experiments test; it does not fit the model or run analyses.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cogpsych-theory-and-hypotheses --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.