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.
git clone --depth 1 https://github.com/heyAyushh/staccWrote 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/rules/heyayushh/stacc/postgresql)<a href="https://agentmods.dev/rules/heyayushh/stacc/postgresql"><img src="https://agentmods.dev/badge/rules/heyayushh/stacc/postgresql/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/rules/heyayushh/stacc/postgresql"><img src="https://agentmods.dev/badge/rules/heyayushh/stacc/postgresql.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 | $0.00000 | $0.02338 |
| Opus 5.5 | $0.00000 | $0.00935 |
| Sonnet 5.5 | $0.00000 | $0.00468 |
| Haiku 4.5 | $0.00000 | $0.00234 |
Grade A, and why
postgresql 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.
This is a copy
100% identical to postgresql — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PostgreSQL Best Practices
This document outlines the mandatory best practices for all PostgreSQL SQL development. Adherence ensures consistency, readability, performance, and maintainability across our codebase.
1. Code Organization and Structure
1.1. Naming Conventions
Always use snake_case for all database identifiers (tables, columns, functions, schemas). SQL keywords must be lowercase. Keep names descriptive but concise.
❌ BAD:
CREATE TABLE UserData (
UserID INT PRIMARY KEY,
UserName VARCHAR(255)
);
SELECT UserID, UserName FROM UserData;
✅ GOOD:
create table user_data (
user_id bigint generated always as identity primary key,
user_name text not null
);
select user_id, user_name from user_data;
1.2. Formatting
Structure queries for maximum readability. Root keywords (SELECT, FROM, WHERE) belong on their own line, with arguments indented. Use explicit AS for all aliases.
❌ BAD:
SELECT t.client_id, DATE(t.created_at) day FROM telemetry t, users u WHERE t.user_id = u.id AND t.submission_date > '2019-07-01' GROUP BY 1, 2;
✅ GOOD:
select
t.client_id as client_id,
date(t.created_at) as day
from
telemetry as t
inner join
users as u
on t.user_id = u.id
where
t.submission_date > '2019-07-01'
and t.sample_id = '10'
group by
t.client_id,
day;
1.3. Comments
Use block comments (/* ... */) for multi-line descriptions and line comments (--) for single-line notes.
/*
This query retrieves active users and their recent orders.
It joins the users table with the orders table.
*/
select
u.user_id, -- Unique user identifier
u.user_name,
o.order_id,
o.order_date
from
users as u
inner join
orders as o
on u.user_id = o.user_id;
2. Common Patterns and Anti-patterns
2.1. Explicit JOINs
Always use explicit INNER JOIN, LEFT JOIN, RIGHT JOIN, or FULL JOIN. Never use implicit joins in the FROM clause.
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.
- 1mo ago First seen · 361 lines · 0 tokens per session scan A dae7ae4c7e95
postgresql is a cursor rule published in the GitHub repository heyAyushh/stacc (3 stars, last pushed 26d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,338 tokens. A static security scan graded it A with 0 findings. It is 100% identical to postgresql, differing in 2 lines, and is treated as a copy.
Other cursor rules, from other repositories
adapter-features
Database-specific features must be implemented in the specialized adapter only. Base adapters (postgres, mysql, etc.) must remain database-agnostic.
unit-tests-tdd
TDD required for behavior changes; ≥80% package coverage on touched packages; unit-test conventions.
planning-and-delegation
Plan every task first, parallelise independent work, and staff each task with the cheapest model that can do it well.
integration-tests
Human-readable integration test requests; helpers vs httptest; suites/ vs per-DB placement.
postgresql
PostgreSQL production rules. Safe migrations, parameterized queries, TIMESTAMPTZ, proper indexing strategy.
netlify-database-migration-from-extension
Switching to Netlify Database. Reference for the netlify-database skill.