Vector databases · Improve
Improve Vector Databases
Correct the selected embedding, indexing or retrieval behavior while preserving filter isolation, quality and freshness.
MCP library 1.6.1 · Instruction library 1.6.1 · English technical instructions
← Back to searchUse this workflow
Connect Vibe Coding Library to a coding agent that supports MCP over Streamable HTTP. Choose Other / MCP agent for a neutral prompt, or a ready-made Codex or Claude Code invocation. Add your task details below.
Goal
Correct the selected embedding, indexing or retrieval behavior while preserving filter isolation, quality and freshness.
Domain rules
- Centralize embedding/collection compatibility metadata and reject mismatched dimensions/model versions before write/query.
- Enforce tenant filters server-side in the repository's retrieval boundary and cover every query variant with isolation tests.
- Use stable source/chunk IDs and versioned idempotent upserts; reconcile deletes and failed partial batches.
- Tune ANN only against an evaluation dataset and explicit latency/resource budget; preserve a measurable quality floor.
- Perform reindex/migration through staged collection/alias cutover with completeness and quality comparison plus rollback.
Validation
- Run integration tests against the supported vector engine/version, including payload filters, aliases, snapshots, and consistency settings used in production.
- Evaluate retrieval quality and latency under representative filters, concurrency, write load, partial failure, and degraded index state.
- Verify tenant isolation, stale/delete convergence, migration completeness, snapshot restore, and fallback behavior.
Repair and handoff
Reproduce the failing query or ingestion event before changing the owner identified by the audit. Preserve an unchanged query/filter as a control. If embedding preprocessing or model changes, ensure both writers and queries move to the compatible space; matching dimensions alone do not establish compatible embeddings.
For stale data, repair version ordering, partial-batch reconciliation or tombstone handling before tuning ANN. For recall loss, compare equivalent filtered exact/ANN results before changing candidate counts, index parameters or reranking. Retain the declared latency/resource budget and authorization scope throughout.
Give the check step the baseline/candidate configurations, fixed corpus and queries, expected IDs, changed stage and migration/deletion evidence. For a cutover, report completeness and a usable recovery path rather than treating an alias switch as proof of a successful rebuild. Pass the complete patch and verification limits to Patch Checking.
Workflow ID: vector-databases-polish · View the versioned source · Shared workflow and authority rules