real row count, accurate size tag, cross-links

README.md

@@ -1,6 +1,6 @@
 ---
 license: mit
-pretty_name: "Misata EdTech Practice Evalpack (declared learning curve)"
+pretty_name: "EdTech SQL Evaluation (declared learning curve, verified answer key)"
 tags:
   - synthetic
   - text-to-sql
@@ -8,6 +8,8 @@ tags:
   - data-agents
   - tabular
   - sql
+size_categories:
+  - 10K<n<100K
 task_categories:
   - table-question-answering
 configs:
@@ -28,6 +30,8 @@ satisfy them exactly, and every shipped question was re-verified by
 executing its gold SQL against these exact files with DuckDB, an engine
 that shares no code with the generator.
 
+**15,600 rows** across the tables below.
+
 ## What is in it
 
 Tables: students (600 rows), practice_attempts (15,000 rows).
@@ -75,3 +79,20 @@ No real data: fully declaration-generated, offline, deterministic
 Generated with [misata](https://github.com/rasinmuhammed/misata) (MIT).
 Where the approach fails is documented in
 [LIMITATIONS.md](https://github.com/rasinmuhammed/misata/blob/main/LIMITATIONS.md).
+
+
+## The rest of the shelf
+
+Same idea, other domains, every answer re-verified with DuckDB against the
+shipped files:
+
+- [Ecommerce analytics](https://huggingface.co/datasets/rasinmuhammed/ecommerce-analytics-sql-evaluation)
+- [SaaS finance](https://huggingface.co/datasets/rasinmuhammed/saas-finance-sql-evaluation)
+- [EdTech practice](https://huggingface.co/datasets/rasinmuhammed/edtech-sql-evaluation)
+
+If you want ground truth for a regression rather than for SQL, the
+[machine degradation set](https://huggingface.co/datasets/rasinmuhammed/predictive-maintenance-remaining-useful-life)
+carries exact remaining useful life on 100 run-to-failure machines.
+
+Generated by [Misata](https://github.com/rasinmuhammed/misata) (MIT).
+Build your own: [misata.studio](https://www.misata.studio).