Issue Resolution Report — 2026-05-11¶
This report documents the resolution of the five oldest open issues in the repository as requested by the user.
Issues Resolved¶
| Issue # | Title | Action Taken | Status |
|---|---|---|---|
| #186 | Data Copilot: Layered Text-to-SQL architecture | Verified architecture doc and reference implementation; added issue link to metadata. | Resolved |
| #187 | Data Copilot: MCP tool/data standardization blueprint | Verified integration matrix and examples; added issue link to metadata. | Resolved |
| #188 | Data Copilot: Agentic RAG + hybrid retrieval | Deepened multi-hop investigation flow and added business metric example; added issue link to metadata. | Resolved |
| #189 | Data Copilot: Validation and repair guardrails | Verified policy checklist and risk taxonomy; added issue link to metadata. | Resolved |
| #190 | Data Copilot: Answer synthesis schema | Verified Pydantic schema and prompt contract; added issue link to metadata. | Resolved |
Implementation Summary¶
- Issue #186: Confirmed that
docs/architecture/data-copilot-text-to-sql.mdcorrectly defines the 5-layer pipeline anddocs/reference-implementations/data-copilot/skeleton.pyprovides a functional reference. - Issue #187: Confirmed that
docs/knowledge_base/patterns/data-copilot-mcp-tooling.mdprovides the necessary standardization and integration examples. - Issue #188: Enhanced
docs/knowledge_base/patterns/data-copilot-agentic-rag.mdwith detailed multi-hop logic and two real-world examples (Home Finance and Business Metric). - Issue #189: Confirmed that
docs/playbooks/data-copilot-sql-validation.mdincludes the required safety guardrails and risk taxonomy. - Issue #190: Confirmed that
docs/reference-implementations/data-copilot/answer-synthesis-schema.mddefines the standard response schema.
Verification¶
- All modified documents pass the KnowledgeOps contract check (
scripts/check_docs_contract.py). - The Data Copilot reference implementation passed functional tests (
docs/reference-implementations/data-copilot/test_skeleton.py).
- Prepared by: Jules
- Date: 2026-05-11
- Confidence: high