performance-optimization

Performance guidance for the backend, including FastAPI, a Python framework for web services. It covers JSON responses and pagination, which splits large result sets into smaller pages.

In plain words
What is it for?
Use it when optimizing FastAPI endpoints, returning data as JSON, or adding pagination to large results.
Why use it?
It addresses slow responses and the difficulty of handling large datasets efficiently.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/pulkitxchadha/awesome-databricks-mcp/performance-optimization
Clone the repo
git clone --depth 1 https://github.com/PulkitXChadha/awesome-databricks-mcp

Made for: Cursor.

Per session 3,497 This file is loaded in full into every session.
When invoked 3,497 The same file — it is already loaded in full.
Security scan A 1 finding. Scan, not verified.
Origin unknown 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 $0.03497 $0.03497
Opus 5 $0.01749 $0.01749
Sonnet 5 $0.00699 $0.00699
Haiku 4.5 $0.00350 $0.00350

Measured 3d ago against content hash 766c7ce0857a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

performance-optimization scanned grade A with 1 finding 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 3d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

fetch(url, options)
.cursor/rules/performance-optimization.mdc · 536 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 3d ago First seen · 536 lines · 3,497 tokens per session scan A 766c7ce0857a

Subscribe to this mod's changes

performance-optimization is a cursor rule published in the GitHub repository PulkitXChadha/awesome-databricks-mcp (19 stars, last pushed 11mo ago), with no licence file. It adds 3,497 tokens to every session, about $0.0175 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.