MongoDB Agent Skills is an official collection of skills and plugins that help AI coding agents work with MongoDB databases, including Atlas and self-managed deployments. Developers use it for query writing, schema design, query optimization, Atlas Search, and vector search. The catalogue entries are MongoDB’s own agent skills, plugins, and setup instructions.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mongodb/agent-skills --skill mongodb-schema-designgit clone --depth 1 https://github.com/mongodb/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mongodb/agent-skills/mongodb-schema-design)<a href="https://agentmods.dev/skills/mongodb/agent-skills/mongodb-schema-design"><img src="https://agentmods.dev/badge/skills/mongodb/agent-skills/mongodb-schema-design/github.svg" alt="Measured on agentmods" height="20"></a>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.
<a href="https://agentmods.dev/skills/mongodb/agent-skills/mongodb-schema-design"><img src="https://agentmods.dev/badge/skills/mongodb/agent-skills/mongodb-schema-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00127 | $0.02823 |
| Opus 5 | $0.00063 | $0.01411 |
| Sonnet 5 | $0.00025 | $0.00565 |
| Haiku 4.5 | $0.00013 | $0.00282 |
Grade A, and why
mongodb-schema-design 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 9d ago.
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.
This is a copy
100% identical to mongodb-schema-design — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MongoDB Schema Design
Data modeling patterns and anti-patterns for MongoDB, maintained by MongoDB. Bad schema is the root cause of most MongoDB performance and cost issues—queries and indexes cannot fix a fundamentally wrong model.
When to Apply
Reference these guidelines when:
- Designing a new MongoDB schema from scratch
- Migrating from SQL/relational databases to MongoDB
- Reviewing existing data models for performance issues
- Troubleshooting slow queries or growing document sizes
- Deciding between embedding and referencing
- Modeling relationships (one-to-one, one-to-many, many-to-many)
- Implementing tree/hierarchical structures
- Seeing Atlas Schema Suggestions or Performance Advisor warnings
- Hitting the 16MB document limit
- Adding schema validation to existing collections
Quick Reference
1. Schema Anti-Patterns - 3 rules
- antipattern-unnecessary-collections - Splitting homogeneous data into multiple collections is often an anti-pattern; consult this reference to validate whether this is the case.
- antipattern-excessive-lookups - When encountering overly normalized collections that reference each other or frequent and possibly slow $lookup operations, consult this reference to validate whether this is problematic and how to fix it.
- antipattern-unnecessary-indexes - Consult this reference when indexes overlap or are not used by queries, to identify and remove unnecessary indexes that add overhead without benefit.
2. Schema Fundamentals - 4 rules
- fundamental-embed-vs-reference - Consult this reference for approaches to modeling different types of relationships (1:1, 1:few, 1:many, many:many, tree/hierarchical data) and how to decide between embedding and referencing based on access patterns.
- fundamental-document-model - Fundamentals of the document model. Consult this reference when migrating from SQL or other normalized data to a document database like MongoDB.
- fundamental-schema-validation - Consult this reference when creating new collections, or adding validation to existing collections, for example in response to finding inconsistent document structures or data quality issues.
- fundamental-document-size - Consult this reference when documents hit the hard 16MB limit, or when accesses are slower than expected as a result of large documents.
What ships with it
20 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/antipattern-excessive-lookups.md 3.5 KB
- references/antipattern-unnecessary-collections.md 4.1 KB
- references/antipattern-unnecessary-indexes.md 3.7 KB
- references/fundamental-document-model.md 3.5 KB
- references/fundamental-document-size.md 9.6 KB
- references/fundamental-embed-vs-reference.md 15 KB
- references/fundamental-schema-validation.md 4.3 KB
- references/pattern-approximation.md 3.2 KB
- references/pattern-archive.md 5.3 KB
- references/pattern-attribute.md 2.4 KB
- references/pattern-bucket.md 4.2 KB
- references/pattern-computed.md 6.0 KB
- references/pattern-document-versioning.md 5.0 KB
- references/pattern-extended-reference.md 3.3 KB
- references/pattern-outlier.md 5.6 KB
- references/pattern-polymorphic.md 6.0 KB
- references/pattern-schema-versioning.md 8.2 KB
- references/pattern-time-series-collections.md 6.5 KB
- references/source-query-stats.md 3.4 KB
- references/source-slow-query-logs.md 2.3 KB
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.
- 9d ago First seen · 182 lines · 127 tokens per session scan A 2a19fcd1a85b
mongodb-schema-design is a skill published in the GitHub repository mongodb/agent-skills (182 stars, last pushed 6d ago), licensed Apache-2.0. It adds 127 tokens to every session and 2,823 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to mongodb-schema-design, differing in 0 lines, and is treated as a copy.
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