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 agentmods add rules/aiagentwithdhruv/ai-dev-stack/40-cache-redisgit clone --depth 1 https://github.com/aiagentwithdhruv/ai-dev-stackWhat 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 | $0.00000 | $0.00207 |
| Opus 5 | $0.00000 | $0.00103 |
| Sonnet 5 | $0.00000 | $0.00041 |
| Haiku 4.5 | $0.00000 | $0.00021 |
Grade A, and why
40-cache-redis 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 2d 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.
What it actually says
Redis usage:
- Use Redis for caching, rate limiting, session-like ephemeral state, queues, and short-lived coordination.
- Choose TTLs intentionally.
- Cache only what has a clear performance benefit.
- Make cache invalidation explicit.
Rules:
- Wrap Redis access in dedicated utilities/services.
- Use stable key naming conventions.
- Document key patterns if introducing new families of keys.
- Prefer idempotent worker/job behavior.
- Use retries carefully and avoid infinite retry loops.
Caching expectations:
- Cache expensive reads and repeated metadata lookups where appropriate.
- Do not cache highly sensitive data unless encrypted and justified.
- Do not rely on cache as the only source of truth for critical persistent state.
Do not:
- Scatter raw Redis calls across the codebase.
- Store large unbounded payloads without TTL or cleanup strategy.
- Mix queue semantics and cache semantics without clarity.
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.
- 2d ago First seen · 28 lines · 0 tokens per session scan A c2e4fd24cfa0
40-cache-redis is a cursor rule published in the GitHub repository aiagentwithdhruv/ai-dev-stack (10 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 207 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 2026-08-31.
Other cursor rules, from other repositories
cursorrules
You are building an AI/ML project with Python. The project uses PyTorch for model training, handles data pipelines with proper validation, tracks experiments systematically, and follows production ML engineering practices. Code is type-hinted, tested, and reproducible.
cursorrules
Code exhibits taste — Torvalds' term for finding the formulation where special cases disappear. Seek representations where edge cases become impossible, the type system proves correctness, and the API guides users into the pit of success.
angular
Angular: signals, standalone components, RxJS patterns.
django
Django: models, views, ORM best practices.
java
Modern Java: records, sealed classes, streams, virtual threads.
javascript
Modern JavaScript: ES2023+, async patterns, common traps.