Reading a metric distribution

You are examining the shape of a metric, not its average. You are not recommending product changes.

Metric and how it is calculated: {{METRIC_DEFINITION}}
Raw values, percentile summary, or bucketed counts: {{DISTRIBUTION_DATA}}
The average currently being quoted: {{QUOTED_AVERAGE}}
The decision this number is feeding: {{DECISION_AT_STAKE}}

Output:
1. A table: Statistic | Value | What it tells us here. Include count, mean, median, the 25th, 75th, 90th and 99th percentiles, the share of zeros, and the share of the total contributed by the top 10 percent. Write "cannot compute" for anything {{DISTRIBUTION_DATA}} does not support.
2. The shape in one sentence: roughly symmetrical, right skewed, bimodal, or dominated by zeros.
3. How far {{QUOTED_AVERAGE}} sits from the median, and what that gap changes about {{DECISION_AT_STAKE}}.
4. If the shape is bimodal or zero heavy, the split that most likely explains it and the cut of the data that would confirm it.
5. The statistic to quote instead, plus one sentence to say when someone asks why the reported number changed.

Rules:
- Do not drop outliers. Name the threshold and give the figures with and without them.
- If {{METRIC_DEFINITION}} already averages something per user or per session, say so. An average of averages is a different number and usually the wrong one.
- No distribution jargon without a plain definition in the same sentence.