# Dataset Representation

> Analyze how distinct benchmark Cases are distributed across facets, evaluator rules, and provenance.

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
- [Dataset Representation](https://teammately.ai/docs/benchmark-datasets/representation.md): Analyze how distinct benchmark Cases are distributed across facets, evaluator rules, and provenance.
- [Benchmark Datasets](https://teammately.ai/docs/benchmark-datasets.md): Select benchmark Cases, inspect representation, and freeze immutable Snapshots for reproducible evidence.
- [Benchmark Dataset Cases](https://teammately.ai/docs/benchmark-datasets/cases.md): Inspect benchmark Case membership, coverage traces, references, and scoped bulk actions.
- [Coverage Management](https://teammately.ai/docs/coverage-management.md): Manage benchmark coverage from setup through representation, Coverage Stories, case review, Case Foundry, and contribution requests.
- [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 Topics](https://teammately.ai/docs/coverage-engineering/project-topics.md): Maintain source-grounded subject areas, editable groups, and Atlas relationships used to organize project and benchmark coverage.

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