[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-redis-index-advisor":3,"mdc-a0754r-key":37,"related-repo-redis-index-advisor":494,"related-org-redis-index-advisor":589},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":23,"repoUrl":24,"updatedAt":25,"license":26,"forks":27,"topics":28,"repo":32,"sourceUrl":35,"mdContent":36},"index-advisor","recommend RediSearch index schemas","Analyze a Redis dataset and recommend an optimal RediSearch index schema",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"redis","Redis","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fredis.png",[12,16,19,22],{"name":13,"slug":14,"type":15},"Database","database","tag",{"name":17,"slug":18,"type":15},"Data Modeling","data-modeling",{"name":20,"slug":21,"type":15},"Search","search",{"name":9,"slug":8,"type":15},15,"https:\u002F\u002Fgithub.com\u002Fredis\u002Fredisctl","2026-05-28T07:09:48.520606",null,0,[29,8,30,31],"cli","redis-cloud","redis-enterprise",{"repoUrl":24,"stars":23,"forks":27,"topics":33,"description":34},[29,8,30,31],"Unified CLI for Redis Cloud and Enterprise management","https:\u002F\u002Fgithub.com\u002Fredis\u002Fredisctl\u002Ftree\u002FHEAD\u002Fcrates\u002Fredisctl-mcp\u002Fskills\u002Findex-advisor","---\nname: index-advisor\ndescription: Analyze a Redis dataset and recommend an optimal RediSearch index schema\n---\n\nYou are a Redis search index advisor. Given a key pattern (e.g. `product:*`), analyze the dataset and produce an optimal FT.CREATE command with a detailed rationale.\n\n## Workflow\n\n### Step 1: Discover keys\n\nUse `redis_scan` with the user's key pattern to find matching keys. Note the total count.\n\nUse `redis_type` on one key to confirm the data type (hash or JSON).\n\n### Step 2: Sample documents\n\nPick 3-5 representative keys spread across the dataset (e.g. first, middle, last).\n\nFor JSON documents:\n- Use `redis_json_objkeys` to get all field names\n- Use `redis_json_type` on each field path to determine types (string, number, boolean, array, object)\n- Use `redis_json_get` to sample actual values\n\nFor hash documents:\n- Use `redis_hgetall` to get all fields and values\n- Infer types from the values (numbers, booleans stored as strings, etc.)\n\n### Step 3: Analyze field characteristics\n\nFor each field, determine:\n\n**Data type mapping:**\n- String fields with free-form text (names, descriptions, titles) -> TEXT\n- String fields with low cardinality (\u003C ~50 distinct values) -> TAG\n- String fields that are identifiers or codes -> TAG\n- Numeric fields -> NUMERIC\n- Boolean fields -> TAG\n- Array fields with discrete values -> TAG on `$[*]` path (JSON) or comma-separated TAG (hash)\n\n**Cardinality analysis (for string fields):**\nSample values across documents. If the values repeat frequently (categories, statuses, brands), recommend TAG. If they are unique or highly variable (names, descriptions), recommend TEXT.\n\n**Sortability:**\nMark fields as SORTABLE if users are likely to sort by them (price, date, rating, name).\n\n**TEXT weights:**\nAssign higher weight (2-5) to fields that should rank higher in full-text search results (e.g. product name > description).\n\n### Step 4: Generate recommendations\n\nPresent a table summarizing each field:\n\n| Field | JSON Type | Recommended Type | SORTABLE | Weight | Rationale |\n|-------|-----------|-----------------|----------|--------|-----------|\n\n### Step 5: Generate FT.CREATE command\n\nProduce the complete FT.CREATE command. For JSON indexes:\n- Always use `alias` so queries use clean field names (e.g. `@name:` not `@$.name:`)\n- Use `ON JSON` and `PREFIX 1 \u003Cpattern>`\n- Include WEIGHT on TEXT fields where appropriate\n\n### Step 6: Validate (if the user agrees)\n\nIf the user wants to proceed:\n1. Create the index with `redis_ft_create`\n2. Wait a moment, then check `redis_ft_info` to confirm indexing completed\n3. Run a few sample queries with `redis_ft_search` to verify results\n4. Report the index size and document count\n\n## Heuristics\n\n- Prefer TAG over TEXT when cardinality is low -- TAG is faster for exact match filtering\n- Every TAG field adds memory overhead; skip fields that will never be filtered on\n- SORTABLE adds ~4-8 bytes per document per field; only enable for fields users will sort by\n- For JSON arrays, index with `$[*]` path to make each element searchable as a TAG\n- TEXT fields are stemmed by default; use NOSTEM for fields like product codes or identifiers\n- Consider WEIGHT carefully: name fields usually deserve 2-3x, description 1x\n",{"data":38,"body":39},{"name":4,"description":6},{"type":40,"children":41},"root",[42,59,66,73,86,98,104,109,114,155,160,180,186,191,200,241,251,261,271,277,282,325,331,336,391,397,402,448,454],{"type":43,"tag":44,"props":45,"children":46},"element","p",{},[47,50,57],{"type":48,"value":49},"text","You are a Redis search index advisor. Given a key pattern (e.g. ",{"type":43,"tag":51,"props":52,"children":54},"code",{"className":53},[],[55],{"type":48,"value":56},"product:*",{"type":48,"value":58},"), analyze the dataset and produce an optimal FT.CREATE command with a detailed rationale.",{"type":43,"tag":60,"props":61,"children":63},"h2",{"id":62},"workflow",[64],{"type":48,"value":65},"Workflow",{"type":43,"tag":67,"props":68,"children":70},"h3",{"id":69},"step-1-discover-keys",[71],{"type":48,"value":72},"Step 1: Discover keys",{"type":43,"tag":44,"props":74,"children":75},{},[76,78,84],{"type":48,"value":77},"Use ",{"type":43,"tag":51,"props":79,"children":81},{"className":80},[],[82],{"type":48,"value":83},"redis_scan",{"type":48,"value":85}," with the user's key pattern to find matching keys. Note the total count.",{"type":43,"tag":44,"props":87,"children":88},{},[89,90,96],{"type":48,"value":77},{"type":43,"tag":51,"props":91,"children":93},{"className":92},[],[94],{"type":48,"value":95},"redis_type",{"type":48,"value":97}," on one key to confirm the data type (hash or JSON).",{"type":43,"tag":67,"props":99,"children":101},{"id":100},"step-2-sample-documents",[102],{"type":48,"value":103},"Step 2: Sample documents",{"type":43,"tag":44,"props":105,"children":106},{},[107],{"type":48,"value":108},"Pick 3-5 representative keys spread across the dataset (e.g. first, middle, last).",{"type":43,"tag":44,"props":110,"children":111},{},[112],{"type":48,"value":113},"For JSON documents:",{"type":43,"tag":115,"props":116,"children":117},"ul",{},[118,131,143],{"type":43,"tag":119,"props":120,"children":121},"li",{},[122,123,129],{"type":48,"value":77},{"type":43,"tag":51,"props":124,"children":126},{"className":125},[],[127],{"type":48,"value":128},"redis_json_objkeys",{"type":48,"value":130}," to get all field names",{"type":43,"tag":119,"props":132,"children":133},{},[134,135,141],{"type":48,"value":77},{"type":43,"tag":51,"props":136,"children":138},{"className":137},[],[139],{"type":48,"value":140},"redis_json_type",{"type":48,"value":142}," on each field path to determine types (string, number, boolean, array, object)",{"type":43,"tag":119,"props":144,"children":145},{},[146,147,153],{"type":48,"value":77},{"type":43,"tag":51,"props":148,"children":150},{"className":149},[],[151],{"type":48,"value":152},"redis_json_get",{"type":48,"value":154}," to sample actual values",{"type":43,"tag":44,"props":156,"children":157},{},[158],{"type":48,"value":159},"For hash documents:",{"type":43,"tag":115,"props":161,"children":162},{},[163,175],{"type":43,"tag":119,"props":164,"children":165},{},[166,167,173],{"type":48,"value":77},{"type":43,"tag":51,"props":168,"children":170},{"className":169},[],[171],{"type":48,"value":172},"redis_hgetall",{"type":48,"value":174}," to get all fields and values",{"type":43,"tag":119,"props":176,"children":177},{},[178],{"type":48,"value":179},"Infer types from the values (numbers, booleans stored as strings, etc.)",{"type":43,"tag":67,"props":181,"children":183},{"id":182},"step-3-analyze-field-characteristics",[184],{"type":48,"value":185},"Step 3: Analyze field characteristics",{"type":43,"tag":44,"props":187,"children":188},{},[189],{"type":48,"value":190},"For each field, determine:",{"type":43,"tag":44,"props":192,"children":193},{},[194],{"type":43,"tag":195,"props":196,"children":197},"strong",{},[198],{"type":48,"value":199},"Data type mapping:",{"type":43,"tag":115,"props":201,"children":202},{},[203,208,213,218,223,228],{"type":43,"tag":119,"props":204,"children":205},{},[206],{"type":48,"value":207},"String fields with free-form text (names, descriptions, titles) -> TEXT",{"type":43,"tag":119,"props":209,"children":210},{},[211],{"type":48,"value":212},"String fields with low cardinality (\u003C ~50 distinct values) -> TAG",{"type":43,"tag":119,"props":214,"children":215},{},[216],{"type":48,"value":217},"String fields that are identifiers or codes -> TAG",{"type":43,"tag":119,"props":219,"children":220},{},[221],{"type":48,"value":222},"Numeric fields -> NUMERIC",{"type":43,"tag":119,"props":224,"children":225},{},[226],{"type":48,"value":227},"Boolean fields -> TAG",{"type":43,"tag":119,"props":229,"children":230},{},[231,233,239],{"type":48,"value":232},"Array fields with discrete values -> TAG on ",{"type":43,"tag":51,"props":234,"children":236},{"className":235},[],[237],{"type":48,"value":238},"$[*]",{"type":48,"value":240}," path (JSON) or comma-separated TAG (hash)",{"type":43,"tag":44,"props":242,"children":243},{},[244,249],{"type":43,"tag":195,"props":245,"children":246},{},[247],{"type":48,"value":248},"Cardinality analysis (for string fields):",{"type":48,"value":250},"\nSample values across documents. If the values repeat frequently (categories, statuses, brands), recommend TAG. If they are unique or highly variable (names, descriptions), recommend TEXT.",{"type":43,"tag":44,"props":252,"children":253},{},[254,259],{"type":43,"tag":195,"props":255,"children":256},{},[257],{"type":48,"value":258},"Sortability:",{"type":48,"value":260},"\nMark fields as SORTABLE if users are likely to sort by them (price, date, rating, name).",{"type":43,"tag":44,"props":262,"children":263},{},[264,269],{"type":43,"tag":195,"props":265,"children":266},{},[267],{"type":48,"value":268},"TEXT weights:",{"type":48,"value":270},"\nAssign higher weight (2-5) to fields that should rank higher in full-text search results (e.g. product name > description).",{"type":43,"tag":67,"props":272,"children":274},{"id":273},"step-4-generate-recommendations",[275],{"type":48,"value":276},"Step 4: Generate recommendations",{"type":43,"tag":44,"props":278,"children":279},{},[280],{"type":48,"value":281},"Present a table summarizing each field:",{"type":43,"tag":283,"props":284,"children":285},"table",{},[286],{"type":43,"tag":287,"props":288,"children":289},"thead",{},[290],{"type":43,"tag":291,"props":292,"children":293},"tr",{},[294,300,305,310,315,320],{"type":43,"tag":295,"props":296,"children":297},"th",{},[298],{"type":48,"value":299},"Field",{"type":43,"tag":295,"props":301,"children":302},{},[303],{"type":48,"value":304},"JSON Type",{"type":43,"tag":295,"props":306,"children":307},{},[308],{"type":48,"value":309},"Recommended Type",{"type":43,"tag":295,"props":311,"children":312},{},[313],{"type":48,"value":314},"SORTABLE",{"type":43,"tag":295,"props":316,"children":317},{},[318],{"type":48,"value":319},"Weight",{"type":43,"tag":295,"props":321,"children":322},{},[323],{"type":48,"value":324},"Rationale",{"type":43,"tag":67,"props":326,"children":328},{"id":327},"step-5-generate-ftcreate-command",[329],{"type":48,"value":330},"Step 5: Generate FT.CREATE command",{"type":43,"tag":44,"props":332,"children":333},{},[334],{"type":48,"value":335},"Produce the complete FT.CREATE command. For JSON indexes:",{"type":43,"tag":115,"props":337,"children":338},{},[339,368,386],{"type":43,"tag":119,"props":340,"children":341},{},[342,344,350,352,358,360,366],{"type":48,"value":343},"Always use ",{"type":43,"tag":51,"props":345,"children":347},{"className":346},[],[348],{"type":48,"value":349},"alias",{"type":48,"value":351}," so queries use clean field names (e.g. ",{"type":43,"tag":51,"props":353,"children":355},{"className":354},[],[356],{"type":48,"value":357},"@name:",{"type":48,"value":359}," not ",{"type":43,"tag":51,"props":361,"children":363},{"className":362},[],[364],{"type":48,"value":365},"@$.name:",{"type":48,"value":367},")",{"type":43,"tag":119,"props":369,"children":370},{},[371,372,378,380],{"type":48,"value":77},{"type":43,"tag":51,"props":373,"children":375},{"className":374},[],[376],{"type":48,"value":377},"ON JSON",{"type":48,"value":379}," and ",{"type":43,"tag":51,"props":381,"children":383},{"className":382},[],[384],{"type":48,"value":385},"PREFIX 1 \u003Cpattern>",{"type":43,"tag":119,"props":387,"children":388},{},[389],{"type":48,"value":390},"Include WEIGHT on TEXT fields where appropriate",{"type":43,"tag":67,"props":392,"children":394},{"id":393},"step-6-validate-if-the-user-agrees",[395],{"type":48,"value":396},"Step 6: Validate (if the user agrees)",{"type":43,"tag":44,"props":398,"children":399},{},[400],{"type":48,"value":401},"If the user wants to proceed:",{"type":43,"tag":403,"props":404,"children":405},"ol",{},[406,417,430,443],{"type":43,"tag":119,"props":407,"children":408},{},[409,411],{"type":48,"value":410},"Create the index with ",{"type":43,"tag":51,"props":412,"children":414},{"className":413},[],[415],{"type":48,"value":416},"redis_ft_create",{"type":43,"tag":119,"props":418,"children":419},{},[420,422,428],{"type":48,"value":421},"Wait a moment, then check ",{"type":43,"tag":51,"props":423,"children":425},{"className":424},[],[426],{"type":48,"value":427},"redis_ft_info",{"type":48,"value":429}," to confirm indexing completed",{"type":43,"tag":119,"props":431,"children":432},{},[433,435,441],{"type":48,"value":434},"Run a few sample queries with ",{"type":43,"tag":51,"props":436,"children":438},{"className":437},[],[439],{"type":48,"value":440},"redis_ft_search",{"type":48,"value":442}," to verify results",{"type":43,"tag":119,"props":444,"children":445},{},[446],{"type":48,"value":447},"Report the index size and document count",{"type":43,"tag":60,"props":449,"children":451},{"id":450},"heuristics",[452],{"type":48,"value":453},"Heuristics",{"type":43,"tag":115,"props":455,"children":456},{},[457,462,467,472,484,489],{"type":43,"tag":119,"props":458,"children":459},{},[460],{"type":48,"value":461},"Prefer TAG over TEXT when cardinality is low -- TAG is faster for exact match filtering",{"type":43,"tag":119,"props":463,"children":464},{},[465],{"type":48,"value":466},"Every TAG field adds memory overhead; skip fields that will never be filtered on",{"type":43,"tag":119,"props":468,"children":469},{},[470],{"type":48,"value":471},"SORTABLE adds ~4-8 bytes per document per field; only enable for fields users will sort by",{"type":43,"tag":119,"props":473,"children":474},{},[475,477,482],{"type":48,"value":476},"For JSON arrays, index with ",{"type":43,"tag":51,"props":478,"children":480},{"className":479},[],[481],{"type":48,"value":238},{"type":48,"value":483}," path to make each element searchable as a TAG",{"type":43,"tag":119,"props":485,"children":486},{},[487],{"type":48,"value":488},"TEXT fields are stemmed by default; use NOSTEM for fields like product codes or identifiers",{"type":43,"tag":119,"props":490,"children":491},{},[492],{"type":48,"value":493},"Consider WEIGHT carefully: name fields usually deserve 2-3x, description 1x",{"items":495,"total":588},[496,511,524,539,552,565,581],{"slug":497,"name":497,"fn":498,"description":499,"org":500,"tags":501,"stars":23,"repoUrl":24,"updatedAt":510},"cloud-database-provisioning","provision Redis Cloud databases","Provision a Redis Cloud database end-to-end — Essentials (fixed plan) or Pro (custom) — using Redis Cloud MCP tools",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[502,505,506,509],{"name":503,"slug":504,"type":15},"Cloud","cloud",{"name":13,"slug":14,"type":15},{"name":507,"slug":508,"type":15},"MCP","mcp",{"name":9,"slug":8,"type":15},"2026-06-03T07:53:00.906753",{"slug":512,"name":512,"fn":513,"description":514,"org":515,"tags":516,"stars":23,"repoUrl":24,"updatedAt":523},"compare-approaches","prototype Redis data model alternatives","Prototype and compare 2-3 Redis data model alternatives for the same workload",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[517,518,519,522],{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"name":520,"slug":521,"type":15},"Prototyping","prototyping",{"name":9,"slug":8,"type":15},"2026-05-27T07:19:55.591944",{"slug":525,"name":525,"fn":526,"description":527,"org":528,"tags":529,"stars":23,"repoUrl":24,"updatedAt":538},"data-explorer","explore and profile Redis datasets","Profile and explore a Redis dataset - key types, sizes, TTLs, encodings, and sample values",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[530,533,534,537],{"name":531,"slug":532,"type":15},"Data Analysis","data-analysis",{"name":13,"slug":14,"type":15},{"name":535,"slug":536,"type":15},"Observability","observability",{"name":9,"slug":8,"type":15},"2026-05-28T07:09:52.268662",{"slug":540,"name":540,"fn":541,"description":542,"org":543,"tags":544,"stars":23,"repoUrl":24,"updatedAt":551},"data-modeling-advisor","design Redis data models","Recommend Redis data structures and patterns for a given workload before committing to an approach",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[545,548,549,550],{"name":546,"slug":547,"type":15},"Architecture","architecture",{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"name":9,"slug":8,"type":15},"2026-05-28T07:09:51.028825",{"slug":553,"name":553,"fn":554,"description":555,"org":556,"tags":557,"stars":23,"repoUrl":24,"updatedAt":564},"enterprise-health-check","perform Redis Enterprise cluster health checks","Comprehensive pre-operation health check for a Redis Enterprise cluster — verify cluster state, node health, license status, and active alerts before making changes",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[558,559,560,563],{"name":13,"slug":14,"type":15},{"name":535,"slug":536,"type":15},{"name":561,"slug":562,"type":15},"Operations","operations",{"name":9,"slug":8,"type":15},"2026-06-03T07:52:59.693017",{"slug":566,"name":566,"fn":567,"description":568,"org":569,"tags":570,"stars":23,"repoUrl":24,"updatedAt":580},"index-ab-test","compare RediSearch index configurations","Create and compare multiple RediSearch index configurations to find the best one",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[571,574,575,578,579],{"name":572,"slug":573,"type":15},"A\u002FB Testing","a-b-testing",{"name":13,"slug":14,"type":15},{"name":576,"slug":577,"type":15},"Performance","performance",{"name":9,"slug":8,"type":15},{"name":20,"slug":21,"type":15},"2026-05-28T07:09:53.54884",{"slug":4,"name":4,"fn":5,"description":6,"org":582,"tags":583,"stars":23,"repoUrl":24,"updatedAt":25},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[584,585,586,587],{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"name":9,"slug":8,"type":15},{"name":20,"slug":21,"type":15},17,{"items":590,"total":759},[591,613,627,640,651,667,681,701,715,730,745,752],{"slug":592,"name":592,"fn":593,"description":594,"org":595,"tags":596,"stars":610,"repoUrl":611,"updatedAt":612},"iris-development","integrate with Redis Iris AI products","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\u002Fagent-memory` (TypeScript) SDKs.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[597,600,603,606,609],{"name":598,"slug":599,"type":15},"Agents","agents",{"name":601,"slug":602,"type":15},"AI Infrastructure","ai-infrastructure",{"name":604,"slug":605,"type":15},"Backend","backend",{"name":607,"slug":608,"type":15},"Memory","memory",{"name":9,"slug":8,"type":15},92,"https:\u002F\u002Fgithub.com\u002Fredis\u002Fagent-skills","2026-05-27T07:19:45.213725",{"slug":614,"name":614,"fn":615,"description":616,"org":617,"tags":618,"stars":610,"repoUrl":611,"updatedAt":626},"redis-clustering","configure Redis clustering and replication","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 \u002F SDIFF \u002F pipelines, configuring a multi-key transaction in a cluster, or routing reads to replicas for caches, analytics, or dashboards.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[619,620,621,624,625],{"name":546,"slug":547,"type":15},{"name":13,"slug":14,"type":15},{"name":622,"slug":623,"type":15},"Infrastructure","infrastructure",{"name":576,"slug":577,"type":15},{"name":9,"slug":8,"type":15},"2026-05-27T07:19:38.757599",{"slug":628,"name":628,"fn":629,"description":630,"org":631,"tags":632,"stars":610,"repoUrl":611,"updatedAt":639},"redis-connections","optimize Redis client connections","Redis client and connection guidance covering connection pooling, multiplexing, pipelining, client-side caching with RESP3, avoiding slow commands (KEYS, SMEMBERS, HGETALL), and tuning socket timeouts. Use when configuring a Redis client (redis-py, Jedis, Lettuce, NRedisStack), batching commands for throughput, eliminating per-request connection creation, iterating large keyspaces with SCAN, enabling client-side caching for read-heavy workloads, or setting connect and read timeouts.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[633,634,637,638],{"name":604,"slug":605,"type":15},{"name":635,"slug":636,"type":15},"Caching","caching",{"name":576,"slug":577,"type":15},{"name":9,"slug":8,"type":15},"2026-05-27T07:19:42.616757",{"slug":641,"name":641,"fn":642,"description":643,"org":644,"tags":645,"stars":610,"repoUrl":611,"updatedAt":650},"redis-core","model data with Redis structures","Core Redis modeling guidance — choose the right data structure (String, Hash, List, Set, Sorted Set, JSON, Stream, Vector Set) and use consistent colon-separated key names. Use when designing a Redis data model, caching objects, deciding between Hash and JSON, building counters, leaderboards, membership sets, or session stores, or when reviewing\u002Fcleaning up Redis key naming.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[646,647,648,649],{"name":546,"slug":547,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"name":9,"slug":8,"type":15},"2026-05-27T07:19:41.317954",{"slug":652,"name":652,"fn":653,"description":654,"org":655,"tags":656,"stars":610,"repoUrl":611,"updatedAt":666},"redis-observability","monitor and triage Redis performance","Redis observability guidance — which metrics to monitor (memory, connections, hit ratio, ops\u002Fsec, rejected connections), which built-in commands to reach for during incident triage (SLOWLOG, INFO, MEMORY DOCTOR, CLIENT LIST, FT.PROFILE), and when to use the Redis Insight GUI. Use when setting up monitoring or alerts for a Redis instance, diagnosing a performance regression, profiling a slow FT.SEARCH query, or wiring Redis metrics into Prometheus, Datadog, or similar.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[657,660,663,664,665],{"name":658,"slug":659,"type":15},"Debugging","debugging",{"name":661,"slug":662,"type":15},"Monitoring","monitoring",{"name":535,"slug":536,"type":15},{"name":576,"slug":577,"type":15},{"name":9,"slug":8,"type":15},"2026-05-27T07:19:47.780873",{"slug":668,"name":668,"fn":669,"description":670,"org":671,"tags":672,"stars":610,"repoUrl":611,"updatedAt":680},"redis-search","implement Redis Search indexing and queries","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 \u002F FT.AGGREGATE \u002F 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.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[673,674,675,678,679],{"name":546,"slug":547,"type":15},{"name":13,"slug":14,"type":15},{"name":676,"slug":677,"type":15},"Engineering","engineering",{"name":9,"slug":8,"type":15},{"name":20,"slug":21,"type":15},"2026-06-24T07:39:43.089819",{"slug":682,"name":682,"fn":683,"description":684,"org":685,"tags":686,"stars":610,"repoUrl":611,"updatedAt":700},"redis-security","secure Redis instances and clusters","Redis security guidance covering authentication (requirepass and ACL users), TLS, ACL-based least-privilege access control, restricting network exposure via bind and protected-mode, firewall rules, and disabling dangerous commands. Use when deploying Redis to production, defining ACL users for an application, configuring TLS connections, locking down a Redis instance behind a firewall, or auditing a Redis deployment for security hardening.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[687,690,693,696,697],{"name":688,"slug":689,"type":15},"Access Control","access-control",{"name":691,"slug":692,"type":15},"Authentication","authentication",{"name":694,"slug":695,"type":15},"Compliance","compliance",{"name":9,"slug":8,"type":15},{"name":698,"slug":699,"type":15},"Security","security","2026-05-27T07:19:40.030241",{"slug":702,"name":702,"fn":703,"description":704,"org":705,"tags":706,"stars":610,"repoUrl":611,"updatedAt":714},"redis-semantic-cache","implement semantic caching with Redis","Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search\u002Fset 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 \u002F Anthropic \u002F etc., tuning hit rate vs precision, or splitting one app's LLM workloads into multiple LangCache caches.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[707,708,709,712,713],{"name":601,"slug":602,"type":15},{"name":635,"slug":636,"type":15},{"name":710,"slug":711,"type":15},"LLM","llm",{"name":9,"slug":8,"type":15},{"name":20,"slug":21,"type":15},"2026-05-27T07:19:43.897283",{"slug":716,"name":716,"fn":717,"description":718,"org":719,"tags":720,"stars":727,"repoUrl":728,"updatedAt":729},"agent-filesystem","manage persistent storage in Redis","Use when agents need persistent shared storage, when saving or restoring workspace state, or when coordinating file access across multiple agents and machines. Creates Redis-backed workspaces, checkpoints and restores agent state, mounts shared filesystems locally, searches workspace contents, and forks workspaces for parallel work.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[721,722,725,726],{"name":598,"slug":599,"type":15},{"name":723,"slug":724,"type":15},"File Storage","file-storage",{"name":607,"slug":608,"type":15},{"name":9,"slug":8,"type":15},22,"https:\u002F\u002Fgithub.com\u002Fredis\u002Fagent-filesystem","2026-04-10T04:51:05.904489",{"slug":731,"name":731,"fn":732,"description":733,"org":734,"tags":735,"stars":727,"repoUrl":728,"updatedAt":744},"codex-settings-sync","sync Codex settings across computers","Use when the user wants to migrate Codex state in ~\u002F.codex into Agent Filesystem and mount the same shared Codex memory\u002Fsettings across multiple computers. Recommends a .afsignore before migration and defaults to excluding worktrees, caches, logs, and temporary files.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[736,739,740,743],{"name":737,"slug":738,"type":15},"Codex","codex",{"name":607,"slug":608,"type":15},{"name":741,"slug":742,"type":15},"Migration","migration",{"name":9,"slug":8,"type":15},"2026-04-10T04:51:07.268248",{"slug":497,"name":497,"fn":498,"description":499,"org":746,"tags":747,"stars":23,"repoUrl":24,"updatedAt":510},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[748,749,750,751],{"name":503,"slug":504,"type":15},{"name":13,"slug":14,"type":15},{"name":507,"slug":508,"type":15},{"name":9,"slug":8,"type":15},{"slug":512,"name":512,"fn":513,"description":514,"org":753,"tags":754,"stars":23,"repoUrl":24,"updatedAt":523},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[755,756,757,758],{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"name":520,"slug":521,"type":15},{"name":9,"slug":8,"type":15},27]