documentdb-indexing
Index-type selection and shape guidance for Azure DocumentDB — when to use single-field, compound (ESR), multikey, wildcard, hashed, 2dsphere, TTL, and vector…
Skill by khelanmodi
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Use cases: cloud, writing, finance
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What's inside
- Skill name
documentdb-indexing- Description
- 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 `$text`. Use when designing or reviewing indexes, choosing an index type for a query pattern, or deciding whether an additional index is worth the write cost.
- License
- MIT
- Instructions
- 21 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- name: "documentdb-indexing" does not match folder "indexing"
Files (12)
- SKILL.md
- index-2dsphere-geospatial.md
- index-compound-esr.md
- index-count-budget.md
- index-hashed-shard-keys.md
- index-lifecycle-drop-hide.md
- index-multikey-arrays.md
- index-pattern-cookbook.md
- index-single-field.md
- index-text-prefer-textsearch.md
- index-ttl-expiry.md
- index-wildcard-dynamic-schemas.md
SKILL.md (first lines)
# Indexing Strategies — Azure DocumentDB Companion skill to `documentdb-query-optimizer`. That skill answers *"why is this query slow?"*; this one answers *"which index should I create, and what shape should it take?"*. Azure DocumentDB supports the standard MongoDB index types. Only `_id` is created automatically — every other index must be created explicitly. Default limit: **64 single-field indexes per collection** (extendable to 300 on request). ## Rules - [index-single-field](index-single-field.md) — When a single-field index is enough; direction, options (`unique`, `sparse`, `partial`, collation). - [index-compound-esr](index-compound-esr.md) — Compound index design via ESR (Equality → Sort → Range); prefer one compound over many singles. - [index-multikey-arrays](index-multikey-arrays.md) — Indexing array fields; the one-array-per-compound (parallel-array) restriction; multikey can't cover queries. - [index-text-prefer-textsearch](index-text-prefer-textsearch.md) — On Azure DocumentDB, prefer the `textSearch` index + `$search` over community `$text` indexes. - [index-wildcard-dynamic-schemas](index-wildcard-dynamic-schemas.md) — Wildcard indexes for truly dynamic schemas; cost vs benefit; scope the prefix. - [index-hashed-shard-keys](index-hashed-shard-keys.md) — Hashed indexes for even distribution; shard-key alignment; range-query caveats. - [index-2dsphere-geospatial](index-2dsphere-geospatial.md) — GeoJSON types, `[longitude, latitude]` order, `$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 → `hideIndex` → `dropIndex`. The `_id` index cannot be dropped. - [index-pattern-cookbook](index-pattern-cookbook.md) — Query-pattern → index-shape cookbook (equality+sort, multi-equality, range+sort, equality+range, hybrid).
From khelanmodi/documentdb-agent-kit, MIT.
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Signals
- Stars
- 0
- Forks
- 1
- Open issues
- 2
- Last commit (this folder)
- Apr 24, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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documentdb-cluster-sharding
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Cite this page
documentdb-indexing skill. Agent Mart. https://agentmart.dev/skills/khelanmodi-documentdb-indexing (last updated 2026-10-24)