database-optimization

database-optimization is a skill for Claude Code from ils15/pantheon-legacy. It costs 25 tokens per session (1,973 once invoked), scanned A, original, MIT.

A guide to improving database speed and reviewing database changes. It covers SQL queries, indexes, query plans, migrations, schemas, and the N+1 problem, where one list operation causes many extra queries.

In plain words
What is it for?
Use it to optimize SQL, inspect indexes and execution plans, detect N+1 queries, review Alembic migrations, design schemas, and plan data migrations.
Why use it?
It helps find slow queries, missing or unnecessary indexes, inefficient repeated queries, and unsafe data changes before they cause performance or reliability problems.

Skill for Claude Code

Written for Claude Code: context: fork in frontmatter.

Good fit Use it to optimize SQL, inspect indexes and execution plans, detect N+1 queries, review Alembic migrations, design schemas, and plan data migrations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ils15/pantheon-legacy/database-optimization
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.

Any agent
npx skills add ils15/pantheon-legacy --skill database-optimization
Clone the repo
git clone --depth 1 https://github.com/ils15/pantheon-legacy

Made for: Claude Code.

Wrote 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.

agentmods badge for database-optimization

README.md
[![agentmods](https://agentmods.dev/badge/skills/ils15/pantheon-legacy/database-optimization/github.svg)](https://agentmods.dev/skills/ils15/pantheon-legacy/database-optimization)
Your own site
<a href="https://agentmods.dev/skills/ils15/pantheon-legacy/database-optimization"><img src="https://agentmods.dev/badge/skills/ils15/pantheon-legacy/database-optimization/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.

agentmods 80×15 button for database-optimization

Your own site · 80×15
<a href="https://agentmods.dev/skills/ils15/pantheon-legacy/database-optimization"><img src="https://agentmods.dev/badge/skills/ils15/pantheon-legacy/database-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,973 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00025 $0.01973
Opus 5.5 $0.00010 $0.00789
Sonnet 5.5 $0.00005 $0.00395
Haiku 4.5 $0.00003 $0.00197

Measured 1mo ago against content hash 8716089e2f69, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

database-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 1mo 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.

.clinerules/skills/database-optimization/SKILL.md · 328 lines

How it starts

The opening of the file, as written. The whole thing — 328 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Database Optimization Skill

When to Use

Use this skill when:

  • Optimizing slow SQL queries
  • Analyzing missing or redundant indexes
  • Reviewing Alembic migrations for safety
  • Identifying N+1 query problems
  • Designing database schemas
  • Planning data migrations
  • Reviewing query execution plans

Optimization Checklist

1. Index Analysis

-- Check missing indexes
SELECT schemaname, tablename, indexname, indexdef
FROM pg_indexes
WHERE tablename = 'your_table';

-- Identify unused indexes
SELECT * FROM pg_stat_user_indexes
WHERE idx_scan = 0;

Index Recommendations:

✅ Always index:
- Primary keys (automatic)
- Foreign keys
- Columns in WHERE clauses
- Columns in ORDER BY
- Columns in JOIN conditions

❌ Avoid indexing:
- Low cardinality columns (boolean, status)
- Frequently updated columns
- Small tables (<1000 rows)

2. N+1 Query Detection

# ❌ N+1 Problem
users = await session.execute(select(User))
for user in users:
    # This triggers N additional queries!
    orders = await session.execute(
        select(Order).where(Order.user_id == user.id)
    )

# ✅ Solution: Eager loading
from sqlalchemy.orm import selectinload

users = await session.execute(
    select(User).options(selectinload(User.orders))
)

3. Query Optimization Patterns

# ✅ Use pagination
from sqlalchemy import select
from app.models import Product

async def get_products(skip: int = 0, limit: int = 20):
    query = select(Product).offset(skip).limit(limit)
    result = await session.execute(query)
    return result.scalars().all()

# ✅ Use specific columns (not SELECT *)
query = select(Product.id, Product.name, Product.price)

# ✅ Use exists() for existence checks
from sqlalchemy import exists
query = select(exists().where(User.email == email))

4. Migration Safety

# ✅ Safe migration patterns
def upgrade():
    # Add column with default (no table lock)
    op.add_column('users', sa.Column('status', sa.String(20), 
                                      server_default='active'))

# ❌ Dangerous patterns
def upgrade():
    # Avoid: Rename column (breaks app)
    op.alter_column('users', 'name', new_column_name='full_name')
    
    # Avoid: Change column type (data loss risk)
    op.alter_column('users', 'age', type_=sa.String())

Read the full file on GitHub · 328 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. 1mo ago First seen · 328 lines · 25 tokens per session scan A 8716089e2f69

Subscribe to this mod's changes

database-optimization is a skill published in the GitHub repository ils15/pantheon-legacy (12 stars, last pushed 26d ago), licensed MIT. It adds 25 tokens to every session and 1,973 once invoked, about $0.0001 per session on Opus 5.5. 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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