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Documentdb Indexing

skill-azure-documentdb-agent-kit-indexing · by Azure

Index-type selection and shape guidance for Azure DocumentDB — when to use single-field, compound (ESR), multikey, wildcard, hashed, 2dsphere, TTL, and vector indexes; query-pattern → index-shape cookbook; per-collection index budget; DocumentDB-specific preference for `textSearch` over community `$text`. Use when designing or reviewing indexes, choosing an index type for a query pattern, or deci…

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Install

$ agentstack add skill-azure-documentdb-agent-kit-indexing

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Indexing Strategies — Azure DocumentDB

Companion skill to documentdb-query-optimizer. That skill answers "why is this query slow?"; this one answers "which index should I create, and what shape should it take?".

Azure DocumentDB supports the standard MongoDB index types. Only _id is created automatically — every other index must be created explicitly. Default limit: 64 single-field indexes per collection (extendable to 300 on request).

Index engine types

> _id vs regular indexes: The _id index is a B-tree, created automatically, and cannot be dropped. For sharded collections the _id key is composite — it includes a hash of the shard key. All other indexes created via createIndex are RUM indexes; the exception is geospatial indexes (2dsphere, 2d), which are GiST indexes.

Rules

  • [index-single-field](index-single-field.md) — When a single-field index is enough; direction, options (unique, sparse, partial, collation).
  • [index-compound-esr](index-compound-esr.md) — Compound index design via ESR (Equality → Sort → Range); prefer one compound over many singles.
  • [index-multikey-arrays](index-multikey-arrays.md) — Indexing array fields; the one-array-per-compound (parallel-array) restriction; multikey can't cover queries.
  • [index-text-prefer-textsearch](index-text-prefer-textsearch.md) — On Azure DocumentDB, prefer the textSearch index + $search over community $text indexes.
  • [index-wildcard-dynamic-schemas](index-wildcard-dynamic-schemas.md) — Wildcard indexes for truly dynamic schemas; cost vs benefit; scope the prefix.
  • [index-hashed-shard-keys](index-hashed-shard-keys.md) — Hashed indexes for even distribution; when sharding becomes necessary; shard-key alignment; range-query caveats.
  • [index-2dsphere-geospatial](index-2dsphere-geospatial.md) — GeoJSON types, [longitude, latitude] order, $near / $geoWithin / $geoIntersects.
  • [index-ttl-expiry](index-ttl-expiry.md) — TTL indexes: expireAfterSeconds semantics, date-field requirement, monitoring.
  • [index-count-budget](index-count-budget.md) — Keep 5–15 indexes per collection; review $indexStats; drop unused.
  • [index-lifecycle-drop-hide](index-lifecycle-drop-hide.md) — Safe lifecycle: inventory → detect redundancy → hideIndexdropIndex. The _id index cannot be dropped.
  • [index-pattern-cookbook](index-pattern-cookbook.md) — Query-pattern → index-shape cookbook

(equality+sort, multi-equality, selectivity ordering, $eq + $in mix, range+sort, equality+range, hybrid, partial index for large arrays).

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.