using-document-databases

using-document-databases is a skill for Claude Code from ancoleman/ai-design-components. It costs 52 tokens per session (2,023 once invoked), scanned A, original, MIT.

A guide to document databases, which store flexible, JSON-like records instead of requiring every record to follow one fixed table structure. It covers MongoDB, DynamoDB, Firestore, indexing, schema design, and aggregation pipelines.

In plain words
What is it for?
Use it for content management, user profiles, product catalogs, event logs, flexible data models, and applications that need nested records or horizontal scaling.
Why use it?
It helps when data shapes change often or naturally contain nested objects. It also helps choose between databases suited to AWS, Firebase, or general-purpose applications.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python scripts/analyze_schema.py --db myapp.

Part of the backend-data-skills plugin — 6 skills shipped together

Good fit Use it for content management, user profiles, product catalogs, event logs, flexible data models, and applications that need nested records or horizontal scaling.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/ancoleman/ai-design-components
agentmods
npx agentmods add skills/ancoleman/ai-design-components/using-document-databases

Made for: Claude Code.

Or install backend-data-skills, the plugin that ships this one along with the rest of its 6 skills.

Wrote this? Show the measurements

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README.md
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
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Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,023 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.02023
Opus 5 $0.00026 $0.01012
Sonnet 5 $0.00010 $0.00405
Haiku 4.5 $0.00005 $0.00202

Measured 6d ago against content hash fbd90354ba5b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

using-document-databases scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (examples/dynamodb-serverless/handler.py, examples/mongodb-fastapi/main.py, scripts/validate_indexes.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/using-document-databases/SKILL.md · 301 lines

How it starts

The opening of the file, as written. The whole thing — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Document Database Implementation

Guide NoSQL document database selection and implementation for flexible schema applications across Python, TypeScript, Rust, and Go.

When to Use This Skill

Use document databases when applications need:

  • Flexible schemas - Data models evolve rapidly without migrations
  • Nested structures - JSON-like hierarchical data
  • Horizontal scaling - Built-in sharding and replication
  • Developer velocity - Object-to-database mapping without ORM complexity

Database Selection

Quick Decision Framework

DEPLOYMENT ENVIRONMENT?
├── AWS-Native Application → DynamoDB
│   ✓ Serverless, auto-scaling, single-digit ms latency
│   ✗ Limited query flexibility
│
├── Firebase/GCP Ecosystem → Firestore
│   ✓ Real-time sync, offline support, mobile-first
│   ✗ More expensive for heavy reads
│
└── General-Purpose/Complex Queries → MongoDB
    ✓ Rich aggregation, full-text search, vector search
    ✓ ACID transactions, self-hosted or managed

Database Comparison

Database Best For Latency Max Item Query Language
MongoDB General-purpose, complex queries 1-5ms 16MB MQL (rich)
DynamoDB AWS serverless, predictable performance <10ms 400KB PartiQL (limited)
Firestore Real-time apps, mobile-first 50-200ms 1MB Firebase queries

See references/mongodb.md for MongoDB details See references/dynamodb.md for DynamoDB single-table design See references/firestore.md for Firestore real-time patterns

Schema Design Patterns

Embedding vs Referencing

Use the decision matrix in references/schema-design-patterns.md

Quick guide:

Relationship Pattern Example
One-to-Few Embed User addresses (2-3 max)
One-to-Many Hybrid Blog posts → comments
One-to-Millions Reference User → events (logging)
Many-to-Many Reference Products ↔ Categories

Read the full file on GitHub · 301 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 301 lines · 52 tokens per session scan A fbd90354ba5b

Subscribe to this mod's changes

using-document-databases is a skill published in the GitHub repository ancoleman/ai-design-components (519 stars, last pushed 9mo ago), licensed MIT. It adds 52 tokens to every session and 2,023 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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