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iris-development

iris-development

github.com/redisAgent workflows1711.7k installsUpdated 7w ago
Repository

About iris-development

A guidance skill for integrating Redis Agent Memory (RAM), a managed Redis Cloud service, into AI agents. It covers session history, semantically searchable long-term memories, and background promotion, with examples for Python and TypeScript SDKs.

Key features

  1. 01Redis Cloud memory setup
  2. 02Session event storage and retrieval
  3. 03Semantic long-term memory search
  4. 04Bulk memory creation and organization
  5. 05Background memory promotion guidance
  6. 06Python and TypeScript SDK examples

Use cases

  1. 01Provisioning a Redis Cloud memory service
  2. 02Connecting an agent to session memory
  3. 03Searching and filtering long-term memories
  4. 04Choosing session events or direct memory writes

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/redis/agent-skills --skill iris-development

After installing, type/iris-developmentin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
ltm-bulk-create.md
ltm-organize.md
ltm-search.md
promotion-overview.md
session-add-event.md
session-retrieval.md
session-when-to-use.md
setup-auth-token.md
setup-cloud-service.md

Details

From the project README

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

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