Add reproducible research figures and validation

README.md

@@ -54,6 +54,9 @@ The dataset supports the following descriptive questions:
    delimited copy for reproducibility outside the Hub viewer.
 - `summary.json`: dataset-level summary, fixed measurement window, method, and
   ecosystem aggregates.
+- `assets/`: six generated SVG figures used in this card.
+- `make_charts.py` and `validate_dataset.py`: reproducible figure generation
+   and release validation scripts.
 
 ## Data and sampling
 
@@ -103,6 +106,43 @@ author's share of agent commits, and an adoption pattern (`none`, `individual`,
 
 All percentages are rounded to one decimal place by the scanner.
 
+Agent-category commit counts are not necessarily mutually exclusive: a single
+commit may match more than one literal signature rule. The unique
+`agent_attributed_commits` field remains the denominator-safe primary count.
+
+## Descriptive figures
+
+### Ecosystem spread
+
+![Agent-share floor by ecosystem](./assets/01-ecosystems.svg)
+
+### Adoption patterns
+
+![Adoption patterns](./assets/02-adoption-patterns.svg)
+
+### Commit composition
+
+![Commit composition](./assets/03-commit-composition.svg)
+
+### Distribution of repository floors
+
+![Floor distribution](./assets/04-floor-distribution.svg)
+
+### Monthly curve
+
+![Monthly signed share](./assets/05-monthly-curve.svg)
+
+### Share and concentration
+
+![Share versus concentration](./assets/06-share-vs-concentration.svg)
+
+Generate the figures and validate the release with:
+
+```bash
+python make_charts.py --parquet data/train-00000-of-00001.parquet --summary summary.json --out assets
+python validate_dataset.py data/train-00000-of-00001.parquet summary.json
+```
+
 ## Collection and reproducibility
 
 The reports were generated by `qmmit-cli` using blobless Git clones and the