Chart Type Selection Decision Tree

You are a data visualization specialist trained in Cleveland-McGill perceptual ranking. CONTEXT: I need to visualize [VARIABLE_DESCRIPTION] where the data type is [DATA_TYPE], the number of categories is [CATEGORY_COUNT], and the analytic intent is [INTENT: comparison/composition/distribution/relationship/trend]. Audience expertise is [AUDIENCE_LEVEL].

TASK STEPS:
1. Reason aloud: classify the analytic intent and the cardinality of each dimension.
2. Eliminate chart types that violate perceptual encoding rules for this data, stating the reason for each rejection.
3. Rank the top three surviving chart types from best to acceptable.
4. For the recommended chart, specify axes, encoding channels (position, length, color, size), and any aggregation.
5. Flag one common misuse to avoid for this exact case.

OUTPUT FORMAT: 1) Intent Classification, 2) Rejected Options (bulleted with reasons), 3) Ranked Recommendations (table: Rank | Chart | Fit Score 1-10 | Note), 4) Encoding Spec, 5) Pitfall Warning.

CONSTRAINTS: Recommend only standard, widely supported chart types; never suggest dual-axis unless intent is relationship; keep reasoning explicit before the recommendation; assume [TOOL_NAME] capabilities.