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/first-fluke/fullstack-starterWrote 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/first-fluke/fullstack-starter/database)<a href="https://agentmods.dev/rules/first-fluke/fullstack-starter/database"><img src="https://agentmods.dev/badge/rules/first-fluke/fullstack-starter/database/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/first-fluke/fullstack-starter/database"><img src="https://agentmods.dev/badge/rules/first-fluke/fullstack-starter/database.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 | $0.00629 |
| Opus 5.5 | $0.00000 | $0.00252 |
| Sonnet 5.5 | $0.00000 | $0.00126 |
| Haiku 4.5 | $0.00000 | $0.00063 |
Grade A, and why
database 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 today.
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:
- database — 86% identical, 8 lines differ
How it starts
The opening of the file, as written. The whole thing — 30 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Standards
Core Rules
- Choose model first, engine second: workload, access pattern, consistency, and scale drive DB selection.
- For relational workloads, enforce at least 3NF by default. Break 3NF only with explicit performance justification.
- For distributed/non-relational workloads, model around aggregates and access paths; document BASE and consistency tradeoffs.
- Document ACID expectations for relational transactions. For distributed tradeoffs, document consistency compromises explicitly.
- For schema architecture work, document the relevant schema layers: external schema, conceptual schema, internal schema.
- Treat integrity as first-class: entity, domain, referential, and business-rule integrity must be explicit.
- Concurrency is never implicit: define transaction boundaries, locking strategy, and isolation level per critical flow.
- For new or changed data models, specify: naming, definition, format, allowed values, and validation rules.
- Update the affected schema decisions and data definitions; add capacity estimates when the task changes capacity requirements.
- Proactively flag anti-patterns and insecure shortcuts instead of silently implementing them.
- Vector DBs are retrieval infrastructure, not source-of-truth databases. Store embeddings and metadata there; keep canonical documents elsewhere.
- Never treat vector search as a drop-in for lexical search. Default to hybrid retrieval when exact match or explainability matters.
- Embeddings are schema-like assets: version model, dimension, chunking, and preprocessing. Plan re-embedding migrations explicitly.
- Schema or data changes on live tables follow expand-contract: additive expand, dual-write + batched backfill, verified read switch, delayed contract. Use lock-aware DDL with timeouts; ship destructive steps in a separate deploy after a soak window.
- Tune queries from measurement and execution plans, never guesswork: measure, explain, nominate the dominant cost node, optimize, re-measure p95.
- Strongly recommend explicit application ownership of business policies, workflows, and external side effects in both new and existing triggers, stored procedures/functions, views, DB jobs, and ORM hooks. For affected existing logic, give a concrete alternative and transition priority; existing convention alone does not justify retention. Use
.agents/skills/oma-db/resources/anti-patterns.md§5 for review and technical retention criteria. This is a strong recommendation, not a blanket feature ban or authorization for an unrelated rewrite. - Preserve DB integrity constraints, atomic updates, transactions/isolation/locking, RLS and privileges, DB audit, justified dependent cascades, and efficient set-based operations. For an accepted transition, follow
.agents/skills/oma-db/resources/migration-playbook.mdto cover every writer, prevent duplicate side effects, and define rollback.
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.
- today Changed · +2 lines 29292e6cbc32
- 1mo ago Changed fa6b15f39c0e
- 1mo ago First seen · 28 lines · 0 tokens per session scan A c5880768939d
database is a cursor rule published in the GitHub repository first-fluke/fullstack-starter (224 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 629 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 2026-09-03.
Other cursor rules, from other repositories
schemas
Sanity schema and Studio config conventions.
supabase-rls
Supabase Row Level Security enforcement.
supabase-db-rls
Guidelines for writing Postgres Row Level Security policies.
supabase-db-create-functions
Guidelines for writing Supabase database functions.
django-orm-for-database-operations
Specifies that Django's ORM should be used for interacting with the database when defining models. This encourages a consistent approach to database operations across the project.
supabase-safety
Supabase migration, RLS and data security constraints.