fnd.r-segmenting-customers
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rsn-learning-outcomes
Extracts insights and improves performance from experience. Applies single-loop (fix action), double-loop (fix frame), reflection (extract insight), experimentation (test belief), and calibration (adjust confidence) modes. Use when correcting mistakes, learning from outcomes, testing hypotheses, or improving predictions. Triggers on "why did this fail", "what can we learn", "test this", "how accurate are we", "pattern of failures".
10fnd.r-scoring-problems
Scores problem severity, frequency, and willingness to pay. Use when ranking problems, validating problem-solution fit, assessing pain intensity, or prioritizing which problems to solve.
5sys-defining-goals
Transforms business strategy (canvas) or natural language into a single measurable goal. Classifies input, extracts intent, derives target using formulas, writes goal file. Does NOT decompose - use sys-decomposing-goals for hierarchy.
5sys-tracking-goals
Monitors active goals against current state. Calculates gaps, scores urgency, detects at-risk goals, generates alerts. Reads goals from strategy/goals/active/, computes progress from metrics, outputs prioritized alerts and updates goal status.
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