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 agentmods add skills/thibautbaissac/rails_ai_agents/performance-optimizationnpx skills add ThibautBaissac/rails_ai_agents --skill performance-optimizationgit clone --depth 1 https://github.com/ThibautBaissac/rails_ai_agentsWrote 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/thibautbaissac/rails_ai_agents/performance-optimization)<a href="https://agentmods.dev/skills/thibautbaissac/rails_ai_agents/performance-optimization"><img src="https://agentmods.dev/badge/skills/thibautbaissac/rails_ai_agents/performance-optimization.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 | $0.00080 | $0.01111 |
| Opus 5 | $0.00040 | $0.00556 |
| Sonnet 5 | $0.00016 | $0.00222 |
| Haiku 4.5 | $0.00008 | $0.00111 |
Grade A, and why
performance-optimization 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.
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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Optimization for Rails 8
Overview
Performance optimization focuses on:
- N+1 query detection and prevention
- Query optimization
- Memory management
- Response time improvements
- Database indexing
Quick Start
# Gemfile
group :development, :test do
gem 'bullet' # N+1 detection
gem 'rack-mini-profiler' # Request profiling
gem 'memory_profiler' # Memory analysis
end
N+1 Query Detection and Prevention
N+1 queries occur when code loads a collection then makes a separate query for each associated record. The Bullet gem detects these automatically. Fix them with eager loading via includes, preload, or eager_load.
Eager Loading Decision Table
| Method | Use When |
|---|---|
includes |
Most cases (Rails chooses best strategy) |
preload |
Forcing separate queries, large datasets |
eager_load |
Filtering on association, need single query |
joins |
Only need to filter, don't need association data |
Key patterns: Bullet configuration, eager loading methods, scoped eager loading, counter caches, N+1 specs with query count assertions.
See references/n-plus-one.md for all code examples and patterns.
Query Optimization
Optimize queries by selecting only needed columns, using batch processing for large datasets, and choosing efficient existence checks.
Key Patterns
| Pattern | Bad | Good |
|---|---|---|
| Column selection | User.all.map(&:name) |
User.pluck(:name) |
| Large iterations | Event.all.each { ... } |
Event.find_each { ... } |
| Existence checks | .any? / .present? |
.exists? |
| Collection size | .length (loads all) |
.size (smart) |
Database Indexing
Add indexes for: foreign keys, columns in WHERE/ORDER BY/JOIN clauses, and unique constraints. Use composite indexes for multi-column queries. Use partial indexes for filtered subsets.
Query Analysis
Use Event.where(...).explain(:analyze) to inspect query plans. Set up slow query logging via ActiveSupport::Notifications to catch queries over a threshold.
What ships with it
3 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.
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.
- 6d ago First seen · 122 lines · 80 tokens per session scan A 235c8cbfabae
performance-optimization is a skill published in the GitHub repository ThibautBaissac/rails_ai_agents (659 stars, last pushed 3mo ago), licensed MIT. It adds 80 tokens to every session and 1,111 once invoked, about $0.0004 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 2026-08-30.
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