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-partners/mongodb-gemini-extension --skill performance_optimizergit clone --depth 1 https://github.com/mongodb-partners/mongodb-gemini-extensionWrote 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-partners/mongodb-gemini-extension/performance_optimizer)<a href="https://agentmods.dev/skills/mongodb-partners/mongodb-gemini-extension/performance_optimizer"><img src="https://agentmods.dev/badge/skills/mongodb-partners/mongodb-gemini-extension/performance_optimizer.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00038 | $0.00977 |
| Opus 5 | $0.00019 | $0.00489 |
| Sonnet 5 | $0.00008 | $0.00195 |
| Haiku 4.5 | $0.00004 | $0.00098 |
Grade A, and why
performance_optimizer 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🚀 MongoDB Performance: Best Practices Guide
A technical manual for developers and architects looking to optimize MongoDB for high-performance, modern applications. This guide covers the essential pillars of horizontal scaling, query optimization, and data modeling.
📖 Overview
MongoDB is the premier NoSQL document database, notable for its flexible JSON-like documents and native horizontal scaling. However, peak performance requires an expert approach to schema design and resource management.
Who should use this guide?
- Seasoned Developers: Transitioning to high-scale MongoDB projects.
- Atlas Users: Optimizing fully managed cloud clusters.
- Self-Managed Teams: Managing local or dedicated MongoDB instances.
🛠 Top 5 Performance Best Practices
1. Examine Query Patterns and Profiling
Performance begins with understanding your application's data access behavior.
- Analyze Patterns: Design your data model based on expected query flow.
- Identify Slow Queries: Use the database profiler or logs to pinpoint bottlenecks.
- Optimization: Store results of frequent sub-queries on documents to reduce read load.
2. Review Data Modeling and Indexing
While MongoDB has a flexible schema, "schema-less" does not mean "design-less."
- Early Planning: Finalize your schema at the start to avoid costly retooling later.
- Versatility: Utilize MongoDB for tabular, geospatial, time-series, and graph data structures.
- Index Coverage: Ensure all regularly queried fields are backed by an appropriate index.
3. Strategy: Embedding vs. Referencing
Deciding how to model relationships is the most critical factor for performance.
| Strategy | Best Use Case | Key Benefit |
|---|---|---|
| Embedding | 1:1 or 1:Many (Small) | Data Locality: Faster reads and atomic single-document writes. |
| Referencing | Many:Many or Large 1:Many | Memory Efficiency: Avoids 16MB limit and reduces RAM pressure. |
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.
- 7d ago First seen · 86 lines · 38 tokens per session scan A 592655e56076
performance_optimizer is a skill published in the GitHub repository mongodb-partners/mongodb-gemini-extension (5 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 38 tokens to every session and 977 once invoked, about $0.0002 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 2026-08-31.
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