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redis-development

Redis performance optimization and best practices. Use this skill when working with Redis data structures, Redis Query Engine (RQE), vector search with RedisVL, semantic caching with LangCache, or optimizing Redis performance.

Install with Tessl CLI

npx tessl i github:redis/agent-skills --skill redis-development
What are skills?

85

Does it follow best practices?

Validation for skill structure

SKILL.md
Review
Evals

Evaluation results

100%

3%

E-commerce Product Search with Redis Query Engine

Redis Query Engine index design and querying

Criteria
Without context
With context

TAG for exact-match fields

100%

100%

TEXT for full-text fields only

100%

100%

NUMERIC for range fields

100%

100%

Minimal field indexing

100%

100%

Key prefix specified

100%

100%

DIALECT 2 used

100%

100%

Specific filters in queries

100%

100%

LIMIT clause used

62%

100%

SORTABLE annotation

100%

100%

RETURN clause used

100%

100%

No wildcard scan queries

100%

100%

Without context: $0.3376 · 1m 43s · 20 turns · 27 in / 4,898 out tokens

With context: $0.3473 · 1m 21s · 18 turns · 2,493 in / 4,074 out tokens

78%

26%

Internal Knowledge Base RAG System

Vector search index configuration and RAG pipeline

Criteria
Without context
With context

Correct vector dimensions

100%

100%

COSINE distance metric

37%

100%

FLOAT32 type specified

100%

42%

HNSW for large dataset

40%

0%

HNSW M parameter set

0%

0%

Key prefix in index

42%

100%

RedisVL for RAG

0%

100%

index.load() for batch insert

0%

100%

VectorQuery with filter

60%

100%

Return fields specified

28%

100%

Context passed to LLM

100%

100%

No client-side vector filtering

100%

100%

Without context: $0.9189 · 5m 29s · 42 turns · 43 in / 12,384 out tokens

With context: $3.1620 · 10m 21s · 100 turns · 101 in / 23,615 out tokens

94%

8%

User Session and Feed Caching Layer

Redis client setup, pipelining, and cache key management

Criteria
Without context
With context

Connection pool used

100%

100%

Single shared client instance

100%

100%

Pipeline for bulk writes

100%

100%

TTL set on cache keys

100%

100%

Colon-separated key names

100%

100%

Short meaningful key names

100%

100%

Hash for multi-field objects

100%

100%

Scan instead of KEYS

100%

100%

Socket timeouts configured

0%

100%

connect timeout < read timeout

0%

0%

No per-request connections

100%

100%

pipeline() not transaction

100%

100%

Without context: $0.5066 · 2m 21s · 27 turns · 33 in / 8,021 out tokens

With context: $0.9160 · 2m 55s · 41 turns · 1,330 in / 9,760 out tokens

Evaluated
Agent
Claude Code

Table of Contents

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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.