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/aiagentwithdhruv/ai-dev-stackWrote 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/aiagentwithdhruv/ai-dev-stack/40-cache-redis)<a href="https://agentmods.dev/rules/aiagentwithdhruv/ai-dev-stack/40-cache-redis"><img src="https://agentmods.dev/badge/rules/aiagentwithdhruv/ai-dev-stack/40-cache-redis/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/aiagentwithdhruv/ai-dev-stack/40-cache-redis"><img src="https://agentmods.dev/badge/rules/aiagentwithdhruv/ai-dev-stack/40-cache-redis.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 | $0.00207 |
| Opus 5.5 | $0.00000 | $0.00083 |
| Sonnet 5.5 | $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 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.
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.
- 1mo 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 (11 stars, last pushed 3mo 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
redis
Redis: data structures, caching patterns, pub/sub.
prisma
Prisma: schema modeling, queries, migrations.
supabase
Supabase: RLS, edge functions, realtime.
convex
Convex: real-time backend, queries, mutations, schema.
database-migrations
Database migrations: safety, rollbacks, zero-downtime.
migration-safety
Migration Safety: database migrations, rollback plans, zero-downtime deploys.