Borrowing it
Nothing to install: this file belongs to Aniket-a14/SRA. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Aniket-a14/SRA/main/.agents/skills/redis-core/SKILL.mdgit clone --depth 1 https://github.com/Aniket-a14/SRAWrote 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/skills/aniket-a14/sra/redis-core)<a href="https://agentmods.dev/skills/aniket-a14/sra/redis-core"><img src="https://agentmods.dev/badge/skills/aniket-a14/sra/redis-core/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/skills/aniket-a14/sra/redis-core"><img src="https://agentmods.dev/badge/skills/aniket-a14/sra/redis-core.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 | $0.00081 | $0.00741 |
| Opus 5.5 | $0.00032 | $0.00296 |
| Sonnet 5.5 | $0.00016 | $0.00148 |
| Haiku 4.5 | $0.00008 | $0.00074 |
Grade A, and why
redis-core 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
92% identical to redis-core — 19 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.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Redis Core
Foundational guidance for modeling data in Redis. Covers data-type selection and key-name conventions — the two decisions that most directly drive memory, performance, and maintainability.
When to apply
- Caching objects, sessions, or per-user state.
- Counters, leaderboards, recent-items lists, unique-membership sets.
- Reviewing or refactoring Redis key names.
- Deciding between a Redis Hash and a JSON document for an entity.
1. Choose the right data structure
Pick the type that matches the access pattern, not just the shape of the data.
| Use case | Recommended type | Why |
|---|---|---|
| Simple values, counters | String | Atomic INCR/DECR, SET/GET |
| Object with independently updated fields | Hash | Per-field reads/writes, no whole-object rewrite |
| Queue, recent-N items | List | O(1) push/pop at ends |
| Unique items, membership checks | Set | O(1) SADD/SISMEMBER/SCARD |
| Rankings, score-based ranges | Sorted Set | Score-ordered; ZADD/ZRANGE/ZRANK |
| Nested / hierarchical data | JSON | Path-level updates, nested arrays, RQE indexing |
| Event log, fan-out messaging | Stream | Persistent, consumer groups |
| Vector similarity | Vector Set | Native vector storage with HNSW |
Common anti-pattern: stuffing a flat object into a serialized string. Updating one field means fetch + parse + mutate + rewrite. Use a Hash instead.
See references/choose-data-structure.md for full rationale and Python/Java examples.
2. Use consistent key names
Use colon-separated segments with a stable hierarchy:
{entity}:{id}:{attribute}
user:1001:profile
user:1001:settings
order:2024:items
session:abc123
article:987:likes
game:space-invaders:leaderboard
Rules of thumb:
- Lowercase, colon-separated. No spaces, no mixed casing (
User_1001_Profileis bad). - Keep keys short but readable — keys live in memory and appear in every command.
- Don't use full URLs or long strings as keys. Extract a short identifier, or use a hash digest of the URL.
- Prefix for multi-tenancy (
tenant:42:user:7:cart) so scans and ACLs can target a tenant cleanly. - Be consistent. Pick one convention per service and apply it across all keys.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 68 lines · 81 tokens per session scan A 7ab1000e7a15
redis-core is a skill published in the GitHub repository Aniket-a14/SRA (24 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 81 tokens to every session and 741 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to redis-core, differing in 19 lines, and is treated as a copy.
Other skills, from other repositories
using-redis-token-buckets
Use when adding a bucket-like rate limit backed by Redis: a per-caller budget with burst capacity and continuous refill, a refund path for requests that did no work, or a limit whose Retry-After must be a real wait rather than a window edge. posthog/tokenbucket.py provides an atomic Lua token bucket (consume, refund…
system-design-data-architecture
Design system data flows and data-layer ownership, consistency, and store choices from access patterns. Use for critical-flow design, DFD semantic review, data lineage, authority, replication, retention, or a data-tier bottleneck. Avoid unrelated framework stream/dataframe implementation questions.
caching
Caching strategies — invalidation, TTL guidelines, cache keys, cache layers, and when not to cache. Use when implementing or reviewing caching logic.
nextjs-app-router
Full end-to-end tRPC setup for Next.js App Router. Covers route handler with fetchRequestHandler (GET + POST exports), TRPCProvider with QueryClientProvider, createTRPCOptionsProxy for RSC prefetching, HydrateClient/HydrationBoundary for hydration, useSuspenseQuery for Suspense, and server-side callers.
subscriptions
Set up real-time event streams with async generator subscriptions using .subscription(async function() { yield }). SSE via httpSubscriptionLink is recommended over WebSocket. Use tracked(id, data) from @trpc/server for reconnection recovery with lastEventId. WebSocket via wsLink and createWSClient from @trpc/client…
client-setup
Create a vanilla tRPC client with createTRPCClient (), configure link chain with httpBatchLink/httpLink, dynamic headers for auth, transformer on links (not client constructor). Infer types with inferRouterInputs and inferRouterOutputs. AbortController signal support. TRPCClientError typing.