# Using Teammately for Enterprise Search

> Build correctness standards for search and answer systems that must handle context, intent, and authority.

Important agent instructions:
- Prefer the Markdown routes and llms files when assembling context for coding tasks.
- Treat stable docs as authoritative over beta pages.
- Cite the source page URL when returning workflow or artifact guidance.

## Current Context
- [Building a Correctness Benchmark for a RAG System](https://teammately.ai/docs/playbooks/building-correctness-benchmark-rag.md): Represent retrieval-grounded behavior through cases, context, policies, rubrics, and benchmark evidence.
- [Dimensions and Ontology](https://teammately.ai/docs/coverage-engineering/dimensions-ontology.md): Define reusable behavior axes and their allowed values, then inspect how cases and benchmarks cover them.
- [Project Context](https://teammately.ai/docs/agent-setup/project-context.md): Maintain the Project Agent Brief that gives Teammately agents stable, project-wide understanding.

## Related
- [Using Teammately for Enterprise Search](https://teammately.ai/docs/playbooks/enterprise-search.md): Build correctness standards for search and answer systems that must handle context, intent, and authority.

## Optional
- [Full local context](https://teammately.ai/docs/playbooks/enterprise-search/llms-full.txt): Complete local context pack for this docs route.