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/zoxknez/ai-coding-rulesWrote 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/zoxknez/ai-coding-rules/63-stack-db)<a href="https://agentmods.dev/rules/zoxknez/ai-coding-rules/63-stack-db"><img src="https://agentmods.dev/badge/rules/zoxknez/ai-coding-rules/63-stack-db/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/zoxknez/ai-coding-rules/63-stack-db"><img src="https://agentmods.dev/badge/rules/zoxknez/ai-coding-rules/63-stack-db.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 | $0.00576 |
| Opus 5.5 | $0.00000 | $0.00230 |
| Sonnet 5.5 | $0.00000 | $0.00115 |
| Haiku 4.5 | $0.00000 | $0.00058 |
Grade A, and why
63-stack-db 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- 63-stack-db — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Rules
Migrations
- Use transactions where supported.
- Ensure down migrations are safe or explicitly irreversible.
- Schema changes require migrations — no manual DB edits.
Queries
- Prefer parameterized queries — never concatenate user input.
- Document performance-critical queries with EXPLAIN output.
- Avoid
SELECT *— select only needed fields.
Indexes
- Add indexes only for real query patterns.
- Verify cardinality and expected benefit before adding.
- Index columns used in WHERE, JOIN, and ORDER BY clauses.
Data Integrity
- Use PRIMARY KEY, FOREIGN KEY, UNIQUE, CHECK constraints.
- Handle cascade deletes deliberately — document behavior.
- Prefer soft deletes (
deleted_at) for recoverable data.
Supabase RLS Patterns (Optional)
Apply when working with Supabase Row-Level Security policies.
Enable RLS (MANDATORY)
- Enable RLS on ALL tables with user data
- No exceptions — even admin tables need policies
- Use permissive policies as default
Performance Optimization (CRITICAL)
Function Caching Pattern
-- ❌ BAD: Function called per row — O(N × f(C))
CREATE POLICY "Users see own data"
ON documents FOR SELECT
USING (auth.uid() = user_id);
-- ✅ GOOD: Function cached once — O(N + f(C))
CREATE POLICY "Users see own data"
ON documents FOR SELECT
USING ((SELECT auth.uid()) = user_id);
Impact: 170ms → <10ms on million-row datasets (17x improvement)
Join Direction Optimization
-- ❌ BAD: Subquery evaluated per row
USING (user_id IN (SELECT id FROM team_members WHERE team_id = ...));
-- ✅ GOOD: Array comparison with cached subquery
USING (user_id = ANY(ARRAY(SELECT id FROM team_members WHERE team_id = ...)));
Null User Handling
-- ✅ Always guard against null auth
USING (
auth.uid() IS NOT NULL
AND (SELECT auth.uid()) = user_id
);
Indexing for RLS
- Index ALL columns used in RLS policies
- Priority:
user_id,tenant_id,organization_id - Composite indexes for multi-column policies
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 · 86 lines · 0 tokens per session scan A 30a4d4341a61
63-stack-db is a cursor rule published in the GitHub repository zoxknez/ai-coding-rules (29 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 576 tokens. 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.
Other cursor rules, from other repositories
as-contract-cast-smell
// ❌ WRONG — bypasses the family ContractSerializer seam const contract = JSON.parse(raw) as Contract; const contract = JSON.parse(raw) as Contract .
no-backward-compatibility
Do not add backward-compatibility shims or migration scaffolding.
postgresql
This guide defines the definitive best practices for writing clean, performant, and maintainable PostgreSQL SQL, focusing on modern conventions and avoiding common pitfalls.
ehs-ims-conventions
EHS IMS app — RBAC, data layer, tRPC, migrations, AI boundaries.
sync-timedb-archive-janitor-contract
Day-close / cold-path worker contracts for synctimedb (A invariants; B tick coordinator retired).
schema
Scalable and secure schema design patterns for relational databases, NoSQL, and APIs. / TR: İlişkisel veri tabanları, NoSQL ve API'ler için ölçeklenebilir ve güvenli şema tasarım kalıpları.