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/gracefullight/docusaurus-pluginsWrote 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/gracefullight/docusaurus-plugins/database)<a href="https://agentmods.dev/rules/gracefullight/docusaurus-plugins/database"><img src="https://agentmods.dev/badge/rules/gracefullight/docusaurus-plugins/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/gracefullight/docusaurus-plugins/database"><img src="https://agentmods.dev/badge/rules/gracefullight/docusaurus-plugins/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 | $0.00368 |
| Opus 5.5 | $0.00000 | $0.00147 |
| Sonnet 5.5 | $0.00000 | $0.00074 |
| Haiku 4.5 | $0.00000 | $0.00037 |
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 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
86% identical to database — 10 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.
What it actually says
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.
- Always document the three 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.
- Data standards are mandatory: naming, definition, format, allowed values, and validation rules.
- Maintain living artifacts: glossary, schema decision log, and capacity estimation — update whenever the model changes.
- 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.
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 · 26 lines · 0 tokens per session scan A 458386e74ecc
database is a cursor rule published in the GitHub repository gracefullight/docusaurus-plugins (23 stars, last pushed 24d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 368 tokens. A static security scan graded it A with 0 findings. It is 86% identical to database, differing in 10 lines, and is treated as a copy.
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