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/dhaupin/vant/vant-skill-redisnpx skills add dhaupin/vant --skill vant-skill-redisgit clone --depth 1 https://github.com/dhaupin/vantWrote 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/dhaupin/vant/vant-skill-redis)<a href="https://agentmods.dev/skills/dhaupin/vant/vant-skill-redis"><img src="https://agentmods.dev/badge/skills/dhaupin/vant/vant-skill-redis.svg" alt="Measured on agentmods" 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 | $0.00007 | $0.00353 |
| Opus 5 | $0.00003 | $0.00177 |
| Sonnet 5 | $0.00001 | $0.00071 |
| Haiku 4.5 | $0.00001 | $0.00035 |
Grade A, and why
redis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Redis
In-memory data store.
When To Use
- Caching
- Sessions
- Real-time
- Rate limiting
What To Do
1. Connect
import { createClient } from 'redis'
const client = createClient({
url: 'redis://localhost:6379'
})
await client.connect()
2. Operations
| Command | What |
|---|---|
| get/set | String values |
| hget/hset | Hash values |
| lpush/lrange | Lists |
| sadd/smembers | Sets |
| publish | Pub/sub |
3. Patterns
// Cache
await client.set('user:1', JSON.stringify(user))
const user = JSON.parse(await client.get('user:1'))
// Session
await client.setex(`sess:${id}`, 3600, data)
// Rate limit
const count = await client.incr(`ratelimit:${key}`)
4. Use Cases
| Use | Benefit |
|---|---|
| Cache DB | Speed |
| Session store | Speed |
| Pub/Sub | Real-time |
| Rate limit | Security |
Output
## Redis
| Key | Type | TTL |
|-----|------|-----|
| user:1 | string | [n]s |
### operations
- [n] total
Role: Redis Operator
Input: Keys, values
Output: Fast data
In-memory speed.
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.
- 5d ago First seen · 92 lines · 7 tokens per session scan A c7c5d4fdacb4
redis is a skill published in the GitHub repository dhaupin/vant (9 stars, last pushed 6d ago), licensed MIT. It adds 7 tokens to every session and 353 once invoked, about $0.0000 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 2026-08-31.
Other skills, from other repositories
nw-database-technology-selection
Database comparison catalogs, RDBMS vs NoSQL selection criteria, CAP/ACID/BASE theory, OLTP vs OLAP, and technology-specific characteristics.
database-redis
Optimize Redis as cache and coordination infrastructure with TTL, eviction, and latency-aware key design. Use when implementing Redis caching, key invalidation, or Redis performance work.
continuum-memory
Configure and use Continuum's two-tier memory system — mem0+Qdrant/Milvus for long-term facts, Redis for short-term sessions, with multi-tenant scopes (USER / AGENT / SHARED / RUN / CONVERSATION). Invoke when the user asks about "remember", "user preferences", "long-term memory", "vector search over memories"…
commit
Atomic git commit with conventional message. Use when the user says "commit", "save my changes", "commit this", or wants to create a git commit. Stages specific files, writes a conventional commit message with body explaining non-obvious decisions. Never uses git add -A.
python-run
Run and debug Python scripts in the project. Use when the user says "run python", "execute this script", "debug this py file", or wants to run/modify a .py file. Handles dependency checks, linting, execution, and error analysis.
V3 Memory Unification
Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).