muse

Theory of Change causal reasoning methodology for logic model generation. Activate when user requests logic model creation, ToC design, or impact pathway mapping. Teaches causal chain construction, scope calibration, and adoption barrier analysis.

Make a measurement recipe (steps, data-collection method, frequency, target, cautions) that an M&E beginner can actually execute. Use when generating recipe items for a metric, prioritizing simple first-step procedures, lightweight data collection, plain language, and a realistic first measurement cycle over methodological rigor.

Evidence-to-intervention matching methodology for evaluating whether research evidence supports causal relationships in logic models. Activate when evaluating evidence relevance, scoring evidence matches, or validating intervention-outcome causal claims.

Evidence presentation and communication methodology for explaining research findings to users. Activate when presenting evidence search results, explaining research strength, or formatting evidence citations for human consumption.