MongoDB Best Practices

SkillDatabases & data

Apply MongoDB data-modeling, indexing, and query rules from access patterns. Use when designing schemas, choosing embed vs reference, or tuning MongoDB query behavior.

Available today. Use it from your connected AI after setup.

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Then ask your AI: use the MongoDB Best Practices skill

What this skill tells your AI

The instructions your AI receives, as published by hoangnguyen0403/agent-skills-standard in skills/database/database-mongodb/SKILL.md and read by ahel’s review.

Priority: P0 (CRITICAL)

Rules

  • Model from access patterns: data read together should usually live together.
  • Embed for bounded one-to-few data; reference for unbounded growth or independent lifecycle.
  • Build indexes for real queries, not theoretical flexibility. Use ESR ordering for equality -> sort -> range compound indexes.
  • Use transactions only when single-document guarantees are insufficient.

Verify

  • Embed vs reference choice matches cardinality and lifecycle.
  • Compound index order matches equality -> sort -> range access.
  • Large pagination uses cursor patterns, not deep skip().
  • Explain output supports the chosen indexes; review keysExamined and docsExamined.
  • Unbounded arrays and hot shard keys were reviewed.

Anti-Patterns

  • No unbounded arrays: Use $push with $slice or redesign using Bucket Pattern.
  • No client-side filtering: Project only needed fields; never fetch full docs to filter in memory.
  • No deep nesting: Keep nesting ≤4 levels; flatten paths that frequently queried.
  • No index cargo cult: each index must map to a read path and write tradeoff.

References

Signals

GitHub stars
565
Forks
164
Last commit
Sep 2026

ahel review

  • S4info
    community integration — published by hoangnguyen0403, not mongodb

Automated review, not a security audit. Ruleset v1.

Advanced
Catalog kind
skill
Gateway key
database-mongodb
Source
github.com/hoangnguyen0403/agent-skills-standard