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redis

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• 9 skills
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• 1 week ago last updated

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   Add Command · redis bundle

   Use when adding a new Redis command (or RediSearch / TimeSeries / VectorSet / module subcommand) to go-redis — covers fetching the command spec and docs, the Cmder type, Cmdable interface wiring, RESP parsing, tests, and the custom-vet rule that enforces SetVal.
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   Commit Style · redis

   Use when writing a commit message or opening a PR in the go-redis repo — covers the Conventional-Commit format, the repo's scope vocabulary (pool, conn, sentinel, command, …), breaking-change syntax, and the rule that NO AI-attribution trailer is added.
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   Prepare Release · redis

   Use when preparing a go-redis release — cutting a new version, bumping version.go, updating the go-redis dependency version in submodule go.mod files, or writing the RELEASE-NOTES.md entry for a new vX.Y.Z. Covers choosing the next semver, finding the last release and gathering merged PRs since then, the release-notes format and what to exclude, running scripts/release.sh to bump versions, and verifying with the scripts/tag.sh dry-run. Does NOT create tags, push, or commit — publishing stays a manual maintainer step.
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   Update CI Image · redis

   Use when adding, updating, or removing a `redislabs/client-libs-test` image tag used by the test stack — covers every place a Redis version → image-tag mapping lives so local `make test` and GitHub CI stay in sync.
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   Testing · redis

   Use when running go-redis tests of any kind — the full suite, a single test, or a filtered/focused subset (e.g. only cluster, sentinel, or pool specs); bringing up or tearing down the Docker test stack; the e2e maintenance-notifications suite (including the proxy-free logic tests); building or formatting; or setting the REDIS_VERSION / RE_CLUSTER / REDIS_PORT knobs that drive the test image and version gating. Covers how to focus a Ginkgo spec and how to run plain go tests.
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   Redis Semantic Cache · redis bundle

   Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/set via the SDK or REST API, tuning the similarity threshold, separating caches per task type, and filtering with custom attributes. Use when caching LLM completions or RAG answers to cut API cost and latency, building a cache-aside layer in front of OpenAI / Anthropic / etc., tuning hit rate vs precision, or splitting one app's LLM workloads into multiple LangCache caches.
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   Iris Development · redis bundle

   Iris is Redis's umbrella for AI-focused products. Use this skill when integrating with the Iris Redis Agent Memory (RAM) data plane on Redis Cloud — recording session events for an AI agent, creating or searching long-term memories, configuring a memory store, or tuning background memory promotion. Code examples use the official `redis-agent-memory` (Python) and `@redis-iris/agent-memory` (TypeScript) SDKs.
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   Redis Clustering · redis bundle

   Redis Cluster and replication guidance covering hash tags for multi-key operations, avoiding CROSSSLOT errors, and reading from replicas to scale read-heavy workloads. Use when designing keys for a sharded Redis Cluster, debugging CROSSSLOT errors on MGET / SDIFF / pipelines, configuring a multi-key transaction in a cluster, or routing reads to replicas for caches, analytics, or dashboards.
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   Redis Search · redis bundle

   Redis Search guidance covering FT.CREATE schema design, field type selection (TEXT, TAG, NUMERIC, GEO, GEOSHAPE, VECTOR, JSON path), DIALECT 2 query syntax, FT.SEARCH / FT.AGGREGATE / FT.HYBRID command selection, vector similarity with HNSW or FLAT, hybrid retrieval combining lexical and vector ranking, RAG pipelines, zero-downtime index updates via aliases, and debugging with FT.PROFILE and FT.EXPLAIN. Use when defining a search index on Hash or JSON documents, writing FT.SEARCH queries with filters, sorting, aggregation, or vector KNN, tuning HNSW parameters, building a RAG retrieval pipeline, or troubleshooting slow or empty search results.
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