Make the documentation match the code about the "clustered" attribute

README.md

@@ -457,7 +457,7 @@ the same layer, enclose them in an `all` expression so they will all be evaluate
  * `-aD` or `--coalesce-densest-as-needed`: Dynamically combine the densest features from each zoom level into other nearby features to keep large tiles under the 500K size limit. (Again, mostly useful for polygons.)
  * `-aS` or `--coalesce-fraction-as-needed`: Dynamically combine a fraction of features from each zoom level into other nearby features to keep large tiles under the 500K size limit. (Again, mostly useful for polygons.)
  * `-pd` or `--force-feature-limit`: Dynamically drop some fraction of features from large tiles to keep them under the 500K size limit. It will probably look ugly at the tile boundaries. (This is like `-ad` but applies to each tile individually, not to the entire zoom level.) You probably don't want to use this.
- * `-aC` or `--cluster-densest-as-needed`: If a tile is too large, try to reduce its size by increasing the minimum spacing between features, and leaving one placeholder feature from each group.  The remaining feature will be given a `"cluster": true` attribute to indicate that it represents a cluster, a `"point_count"` attribute to indicate the number of features that were clustered into it, and a `"sqrt_point_count"` attribute to indicate the relative width of a feature to represent the cluster. If the features being clustered are points, the representative feature will be located at the average of the original points' locations; otherwise, one of the original features will be left as the representative.
+ * `-aC` or `--cluster-densest-as-needed`: If a tile is too large, try to reduce its size by increasing the minimum spacing between features, and leaving one placeholder feature from each group.  The remaining feature will be given a `"clustered": true` attribute to indicate that it represents a cluster, a `"point_count"` attribute to indicate the number of features that were clustered into it, and a `"sqrt_point_count"` attribute to indicate the relative width of a feature to represent the cluster. If the features being clustered are points, the representative feature will be located at the average of the original points' locations; otherwise, one of the original features will be left as the representative.
 
 ### Dropping tightly overlapping features