Add public Cloudy profile matching sample

README.md

@@ -0,0 +1,37 @@
+# Profile Matching - Public Code Sample
+
+This is a small, dependency-free portfolio excerpt adapted from **Cloudy**, an
+AI-assisted profile and matching service I built for a collaboration platform.
+The production repository is private, so this project intentionally contains
+only the self-contained scoring layer and its tests. It includes no user data,
+credentials, API code, or project-specific infrastructure.
+
+## What it demonstrates
+
+- transparent, explainable matching across skills, interests, location, and
+  shared project tags;
+- input normalisation and explicit handling of incomplete profile data;
+- optional affinity weights that personalise recommendations without changing
+  existing behaviour when no preferences are set;
+- pure business logic separated from database and API concerns;
+- executable tests for normal cases, edge cases, and scoring invariants.
+
+The actual application combines this score with an asynchronous PostgreSQL
+repository layer and uses it to rank potential collaboration matches.
+
+## Run the tests
+
+The sample uses only the Python standard library:
+
+```bash
+python -m unittest -v
+```
+
+## Why this is good code
+
+The model is deliberately small and deterministic. Each function has one
+responsibility, is type annotated, and can be tested without a database, LLM,
+or network access. Missing location data never creates a false positive, and
+the weighted extension remains backwards-compatible with the original Jaccard
+similarity model. That keeps the recommendation logic understandable for users
+and safe to evolve in a larger product.