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 skills/kid-sid/codex-spellbook/redisnpx skills add kid-sid/codex-spellbook --skill redisgit clone --depth 1 https://github.com/kid-sid/codex-spellbookWhat 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 | $0.00038 | $0.04515 |
| Opus 5 | $0.00019 | $0.02257 |
| Sonnet 5 | $0.00008 | $0.00903 |
| Haiku 4.5 | $0.00004 | $0.00451 |
Grade A, and why
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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 544 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Redis Patterns
Redis data structures, caching, pub/sub, and streams for Python async apps.
When to Activate
- Choosing the right Redis data structure for a use case
- Implementing caching (cache-aside, write-through, TTL eviction)
- Using pub/sub or Redis Streams for real-time messaging / SSE
- Building a job queue with SKIP LOCKED semantics
- Writing atomic operations (counters, rate limits, distributed locks)
- Debugging slow Redis commands or memory bloat
Connection (async redis-py)
import redis.asyncio as redis
# Single connection
client = await redis.from_url("redis://localhost:6379", decode_responses=True)
# Connection pool (recommended for apps)
pool = redis.ConnectionPool.from_url(
"redis://localhost:6379",
decode_responses=True,
max_connections=20,
)
client = redis.Redis(connection_pool=pool)
# Close on shutdown
await client.aclose()
decode_responses=True returns str instead of bytes — use it unless you store binary data.
Data Structure Decision Table
| Structure | Use For | Avoid When |
|---|---|---|
| String | Single values, JSON blobs, counters, distributed locks | Frequently updating one field of many |
| Hash | Objects with multiple fields; partial field reads/writes | >100 fields or deeply nested — use String+JSON instead |
| List | FIFO queues, activity feeds, bounded history | Random access by index — use Sorted Set |
| Set | Unique membership, tag intersections/unions, "online users" | Need ordering or score — use Sorted Set |
| Sorted Set | Leaderboards, priority queues, time-ordered events, rate limiting | Cardinality >10M — memory gets expensive |
| Stream | Durable pub/sub, consumer groups, event log | Simple fire-and-forget — use pub/sub |
| HyperLogLog | Approx unique count (±0.81% error, capped at 12 KB) | Exact count required |
| Bitmap | Per-user boolean flags, daily active user tracking | More than 512 MB of bits |
Data Structures
Strings — single values, counters, JSON blobs
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.
- 3d ago First seen · 544 lines · 38 tokens per session scan A 0cef90c17b90
redis is a skill published in the GitHub repository kid-sid/codex-spellbook (21 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 4,515 once invoked, about $0.0002 per session on Opus 5. 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 2026-08-30.
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