diff --git a/CHANGES.md b/CHANGES.md
index 2c87ca5..0e176a8 100644
--- a/CHANGES.md
+++ b/CHANGES.md
@@ -2,6 +2,7 @@
 
 * Uses prettier `tqdm` output that is now aware of Jupyter notebooks.
 * `bayes.update` now supports `lognorm` and `gamma` distributions in addition to `norm` and `beta`.
+* Allow `zero_inflated` to accept 0 or 1 as probabilities.
 
 ## v0.29 - latest release
 
diff --git a/CLAUDE.md b/CLAUDE.md
index fe9fe1b..eb7d027 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -21,4 +21,6 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
 
 ## Workflow
 - Always run `make format` before committing to ensure code passes formatting checks
-- Update CHANGES.md when adding new features or fixing bugs
\ No newline at end of file
+- Always update `CHANGES.md` when making code changes (bug fixes, new features, etc.)
+- Add changelog entries under the development version section at the top (marked with `- development version`)
+- Follow the existing format: `* Description of change`
diff --git a/squigglepy/distributions.py b/squigglepy/distributions.py
index ec33c5d..3483767 100644
--- a/squigglepy/distributions.py
+++ b/squigglepy/distributions.py
@@ -1796,8 +1796,15 @@ def zero_inflated(p_zero, dist):
      - 0
      - <Distribution> norm(mean=1.5, sd=0.3)
     """
-    if p_zero > 1 or p_zero < 0 or not isinstance(p_zero, float):
+    if isinstance(p_zero, bool) or not isinstance(p_zero, (float, int)):
+        raise ValueError("`p_zero` must be a float or int")
+    if not 0 <= p_zero <= 1:
         raise ValueError("`p_zero` must be between 0 and 1")
+    # Handle edge cases: p_zero=1 means always 0, p_zero=0 means always sample from dist
+    if p_zero == 1:
+        return MixtureDistribution(dists=[0], weights=[1])
+    elif p_zero == 0:
+        return MixtureDistribution(dists=[dist], weights=[1])
     return MixtureDistribution(dists=[0, dist], weights=p_zero)
 
 
diff --git a/squigglepy/utils.py b/squigglepy/utils.py
index 71ca07b..74b9cec 100644
--- a/squigglepy/utils.py
+++ b/squigglepy/utils.py
@@ -32,7 +32,7 @@ def _process_weights_values(weights=None, relative_weights=None, values=None, dr
         weights = relative_weights
         relative = True
 
-    if isinstance(weights, float):
+    if isinstance(weights, (float, int)) and not isinstance(weights, bool):
         weights = [weights]
     elif isinstance(weights, np.ndarray):
         weights = list(weights)