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 Global-mindee/WAY --skill database-optimizationgit clone --depth 1 https://github.com/Global-mindee/WAYWrote 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/global-mindee/way/database-optimization)<a href="https://agentmods.dev/skills/global-mindee/way/database-optimization"><img src="https://agentmods.dev/badge/skills/global-mindee/way/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.
<a href="https://agentmods.dev/skills/global-mindee/way/database-optimization"><img src="https://agentmods.dev/badge/skills/global-mindee/way/database-optimization.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00020 | $0.01333 |
| Opus 5 | $0.00010 | $0.00666 |
| Sonnet 5 | $0.00004 | $0.00267 |
| Haiku 4.5 | $0.00002 | $0.00133 |
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 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Optimization
EXPLAIN Analysis
Always run EXPLAIN ANALYZE before optimizing. Read the output bottom-up.
-- PostgreSQL
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT) SELECT ...;
-- MySQL
EXPLAIN ANALYZE SELECT ...;
Key metrics to watch:
- Seq Scan on large tables = missing index
- Nested Loop with high row count = consider hash/merge join
- Sort without index = add index on sort column
- Rows estimated vs actual divergence = stale statistics, run
ANALYZE
Index Strategies
B-tree (default, most cases)
CREATE INDEX idx_users_email ON users (email);
CREATE INDEX idx_orders_user_date ON orders (user_id, created_at DESC);
Use for: equality, range queries, sorting. Column order matters in composite indexes: put equality columns first, then range/sort columns.
Partial Index (PostgreSQL)
CREATE INDEX idx_orders_pending ON orders (created_at)
WHERE status = 'pending';
Use when queries always filter on a specific condition. Dramatically smaller than full indexes.
GIN (PostgreSQL - arrays, JSONB, full-text)
CREATE INDEX idx_products_tags ON products USING GIN (tags);
CREATE INDEX idx_docs_search ON documents USING GIN (to_tsvector('english', content));
GiST (PostgreSQL - spatial, range types)
CREATE INDEX idx_locations_point ON locations USING GiST (coordinates);
CREATE INDEX idx_events_period ON events USING GiST (tsrange(start_at, end_at));
Covering Index (index-only scans)
-- PostgreSQL
CREATE INDEX idx_users_email_name ON users (email) INCLUDE (name);
-- MySQL
CREATE INDEX idx_users_email_name ON users (email, name);
N+1 Query Detection
Symptom: 1 query to fetch parent + N queries for each child.
# BAD: N+1
users = db.query(User).all()
for user in users:
print(user.orders) # triggers query per user
# GOOD: eager load
users = db.query(User).options(joinedload(User.orders)).all()
// BAD: N+1
const users = await User.findAll();
for (const user of users) {
const orders = await Order.findAll({ where: { userId: user.id } });
}
// GOOD: batch load
const users = await User.findAll({ include: [Order] });
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 · 175 lines · 20 tokens per session scan A 30ce37fb0c4f
database-optimization is a skill published in the GitHub repository Global-mindee/WAY (11 stars, last pushed 2d ago), licensed MIT. It adds 20 tokens to every session and 1,333 once invoked, about $0.0001 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 2026-09-03.
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