redis/agent-skills

iris-development

Iris is Redis's umbrella for AI-focused products.

ソースを見る

使い方

  1. インストールコマンドをコピーし、自分の環境へ導入する前にソースを確認します。
  2. 必要なツール、認証情報、対応環境を原文で確認します。
  3. 入力と成果物を指定し、出力を資料と照合します。
npx skills add https://github.com/redis/agent-skills --skill iris-development

開始前の確認

  • 導入にはモデル契約、API枠、ファイルへのアクセス許可は含まれません。
  • スター数や導入数は活動の指標であり、独立した品質・安全性試験ではありません。
リポジトリの原文

見出し、例、コード、表、リンク、参照画像を含む原文を表示しています。

Iris: Redis Agent Memory

Iris is the umbrella brand for Redis's AI-focused products. This skill currently covers one product in that family: Redis Agent Memory (RAM) — the persistent memory layer for AI agents, delivered as a managed service on Redis Cloud. Additional Iris products will be added as separate sections when they ship.

Redis Agent Memory exposes a REST/JSON data-plane API with two memory tiers:

  • Session memory — append-only conversation history per session (working memory).
  • Long-term memory — semantically searchable records extracted from sessions (or created directly).

A background promotion worker — managed by Redis Cloud — extracts durable facts from session events and writes them into long-term memory.

Official SDKs

All code samples use the official SDKs:

LanguagePackageClassInstall
Pythonredis-agent-memoryAgentMemorypip install redis-agent-memory
TypeScript@redis-iris/agent-memoryAgentMemorynpm add @redis-iris/agent-memory

Both SDKs read the bearer token from AGENT_MEMORY_API_KEY and the default store ID from AGENT_MEMORY_STORE_ID. The production data-plane URL is https://gcp-us-east4.memory.redis.io; the exact URL for your service is also shown in the Cloud console after provisioning.

When to Apply

Reference these guidelines when:

  • Creating a memory service on Redis Cloud (https://cloud.redis.io/#/agent-memory)
  • Wiring an agent to call AgentMemory.add_session_event(...) / addSessionEvent(...)
  • Searching long-term memory with search_long_term_memory(...) / searchLongTermMemory(...)
  • Choosing between session events and direct long-term memory writes

Rule Categories by Priority

PriorityCategoryImpactPrefix
1Setup & Cloud ServiceHIGHsetup-
2Session Memory / EventsHIGHsession-
3Long-Term MemoryHIGHltm-
4Memory PromotionMEDIUMpromotion-

Quick Reference

1. Setup & Cloud Service (HIGH)

2. Session Memory / Events (HIGH)

3. Long-Term Memory (HIGH)

  • `ltm-bulk-create` - Create long-term memories in bulk with idempotent IDs
  • `ltm-search` - Search long-term memory semantically with filters
  • `ltm-organize` - Organize records with namespace, ownerId, topics, and memoryType

4. Memory Promotion (MEDIUM)

How to Use

Read individual rule files under references/ for detailed explanations and code examples:

references/setup-cloud-service.md
references/session-add-event.md
references/promotion-overview.md

Each rule file contains:

  • Brief explanation of why it matters
  • Correct example(s) with Python and TypeScript SDK code
  • Either an "Incorrect" example or "When to use / When NOT needed" guidance
  • Additional context and references

タスクに関連する項目

同じリポジトリから

関連する Skills

すべての Skills
redis
公式

redis-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.

1時間の導入数
2
GitHub Stars
169
更新日
9月8日
redis
公式

redis-core

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/cleaning up Redis key naming.

1時間の導入数
2
GitHub Stars
169
更新日
9月8日
redis
公式

redis-search

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 fi

1時間の導入数
2
GitHub Stars
169
更新日
9月8日
redis
公式

redis-observability

Redis observability guidance — which metrics to monitor (memory, connections, hit ratio, ops/sec, 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.

1時間の導入数
1
GitHub Stars
167
更新日
9月8日