@emmahyde/thinking-patterns/dist/src/schemas/ScientificMethodSchema.js

MCP server combining systematic thinking, mental models, debugging approaches, and stochastic algorithms for comprehensive cognitive pattern support

import { z } from 'zod';
/**
 * Scientific Method Schema
 *
 * Defines the structure for formal hypothesis testing and experimentation
 * following the scientific method. Includes hypothesis formulation, experimental
 * design, prediction testing, and systematic analysis of results.
 */
// Scientific Method Schema
export const VariableSchema = z.object({
    name: z.string().describe("The name of the variable (e.g., 'user conversion rate', 'website latency')."),
    type: z.enum(["independent", "dependent", "controlled", "confounding"]).describe("The role of the variable in the experiment. Independent: the one you change. Dependent: the one you measure. Controlled: the ones you keep constant."),
    operationalization: z.string().optional().describe("A precise description of how the variable will be measured or manipulated (e.g., 'Latency measured as Time to First Byte in ms', 'Conversion measured by sign-ups per 1000 visitors').")
});
export const HypothesisSchema = z.object({
    statement: z.string().describe("A clear, falsifiable statement predicting a relationship between variables (e.g., 'Reducing button size will decrease user conversion rate')."),
    variables: z.array(VariableSchema).describe("An array defining all variables involved in the hypothesis."),
    assumptions: z.array(z.string()).describe("Any conditions assumed to be true for the hypothesis to hold (e.g., 'Users notice button size')."),
    hypothesisId: z.string().describe("A unique identifier for tracking this specific hypothesis."),
    confidence: z.number().min(0).max(1).describe("A prior confidence score (0-1) in the hypothesis before testing."),
    domain: z.string().describe("The specific area of study or context of the hypothesis (e.g., 'UI/UX Optimization')."),
    iteration: z.number().describe("The version number of this hypothesis, for tracking refinements."),
    alternativeTo: z.array(z.string()).optional().describe("A list of IDs of competing or alternative hypotheses."),
    refinementOf: z.string().optional().describe("The ID of a previous, broader hypothesis that this one refines."),
    status: z.enum(["proposed", "testing", "supported", "refuted", "refined"]).describe("The current lifecycle stage of the hypothesis.")
});
export const PredictionSchema = z.object({
    if: z.string().describe("The specific condition or action to be taken in the experiment (e.g., 'If we decrease the button size by 50%')."),
    then: z.string().describe("The specific, measurable outcome expected if the hypothesis is true (e.g., 'then the user conversion rate will drop by at least 5%')."),
    else: z.string().optional().describe("An alternative outcome, which might support a competing hypothesis (e.g., 'else the conversion rate will remain unchanged').")
});
export const ExperimentSchema = z.object({
    design: z.string().describe("A description of the experimental design (e.g., 'A/B Test', 'Repeated Measures Design')."),
    methodology: z.string().describe("The step-by-step procedure for conducting the experiment."),
    predictions: z.array(PredictionSchema).describe("The specific, testable predictions derived from the hypothesis."),
    experimentId: z.string().describe("A unique identifier for this specific experiment."),
    hypothesisId: z.string().describe("The ID of the hypothesis this experiment is designed to test."),
    controlMeasures: z.array(z.string()).describe("Measures taken to prevent confounding variables from influencing the results (e.g., 'Ensuring both user groups have similar demographics')."),
    results: z.string().optional().describe("A summary of the raw data or findings from the experiment."),
    outcomeMatched: z.boolean().optional().describe("A flag indicating whether the results matched the 'then' part of the prediction."),
    unexpectedObservations: z.array(z.string()).optional().describe("Any surprising findings not anticipated by the hypothesis."),
    limitations: z.array(z.string()).optional().describe("Factors that may limit the generalizability of the findings (e.g., 'Sample size was small')."),
    nextSteps: z.array(z.string()).optional().describe("Proposed follow-up actions, such as further experiments or analysis.")
});
export const ScientificMethodSchema = z.object({
    stage: z.enum(["observation", "question", "hypothesis", "experiment", "analysis", "conclusion", "iteration"]).describe("The current stage in the scientific inquiry process."),
    observation: z.string().optional().describe("An initial observation that sparks inquiry (e.g., 'The new feature has lower engagement than expected')."),
    question: z.string().optional().describe("A specific question that arises from the observation (e.g., 'Why is user engagement low?')."),
    hypothesis: HypothesisSchema.optional().describe("The formal hypothesis being investigated."),
    experiment: ExperimentSchema.optional().describe("The design and details of the experiment to test the hypothesis."),
    analysis: z.string().optional().describe("The interpretation of the experimental results and statistical analysis."),
    conclusion: z.string().optional().describe("The final conclusion drawn from the analysis, stating whether the hypothesis was supported or refuted."),
    inquiryId: z.string().describe("A unique identifier for the entire scientific inquiry from observation to conclusion."),
    iteration: z.number().describe("The iteration number of the inquiry process, for tracking cycles of refinement."),
    nextStageNeeded: z.boolean().describe("A flag indicating whether the inquiry requires a subsequent stage.")
});