+# altimate
+
**The open-source data engineering harness.**
The intelligence layer for data engineering AI — 99+ deterministic tools for SQL analysis,
@@ -133,16 +135,7 @@ Transpile SQL between Snowflake, BigQuery, Databricks, Redshift, PostgreSQL, MyS
Automatic column scanning for PII across 15 categories with 30+ regex patterns. Safety checks and policy enforcement before query execution.
### dbt Native
-Manifest parsing, test generation, model scaffolding, incremental model detection, and lineage-aware refactoring. 12 purpose-built skills including medallion patterns, yaml config generation, and dbt docs.
-
-### Data Visualization
-Interactive charts and dashboards from SQL results. The data-viz skill generates publication-ready visualizations with automatic chart type selection based on your data.
-
-### Local-First Tracing
-Built-in observability for AI interactions — trace tool calls, token usage, and session activity locally. No external services required. View traces with `altimate trace`.
-
-### AI Teammate Training
-Teach your AI teammate project-specific patterns, naming conventions, and best practices. The training system learns from examples and applies rules automatically across sessions.
+Manifest parsing, test generation, model scaffolding, incremental model detection, and lineage-aware refactoring. 11 purpose-built skills including medallion patterns, yaml config generation, and dbt docs.
## Agent Modes
@@ -209,6 +202,74 @@ packages/
util/ Shared utilities
```
+## Documentation
+
+Full docs at **[altimate.ai](https://altimate.ai)**.
+
+- [Getting Started](https://altimate.ai/getting-started/)
+- [SQL Tools](https://altimate.ai/data-engineering/tools/sql-tools/)
+- [Agent Modes](https://altimate.ai/data-engineering/agent-modes/)
+- [Configuration](https://altimate.ai/configure/model-providers/)
+
+## Validation
+
+The `/validate` skill lets you audit past AI agent sessions against a set of quality criteria — checking whether the agent's reasoning, tool calls, and final response were correct, grounded, and complete. It pulls conversation traces from the backend, runs them through an evaluation pipeline, and reports per-criterion pass/fail results with details.
+
+You can validate:
+- **A single trace**: `/validate | Criteria | Avg Score | Score Bar | Pass Rate | Status |
|---|---|---|---|---|
| Groundedness | ++ |
| # | Issue | Criteria | Affected Traces |
|---|---|---|---|
| 1 | +
| Trace ID | Overall | Groundedness | Validity | Coherence | Utility | Tool Validation |
|---|---|---|---|---|---|---|