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by redisredis/agent-skills163 stars
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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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Use this Skill: https://skilld.dev/gh/redis/agent-skills/iris-development

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SKILL.md

≈108 tokens always: the name and description. ≈968 when used: this file. ≈8.9k more on demand in 9 files.

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:

Language Package Class Install
Python redis-agent-memory AgentMemory pip install redis-agent-memory
TypeScript @redis-iris/agent-memory AgentMemory npm 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

Priority Category Impact Prefix
1 Setup & Cloud Service HIGH setup-
2 Session Memory / Events HIGH session-
3 Long-Term Memory HIGH ltm-
4 Memory Promotion MEDIUM promotion-

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

Source: SKILL.md on GitHub

Third-party checks

1 warning1mo3 checks · Risk SAFE
  • Gen Agent Trust Hub1mo

    The skill provides comprehensive documentation and code examples for integrating with Redis Agent Memory (RAM) using official Python and TypeScript SDKs. It follows security best practices for credential management and relies on official Redis infrastructure.

  • Socket1mo

    No alerts

  • Snyk1mo

    Risk: MEDIUM · 1 issue

Provenance

Signed by skilld at d20b723. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 3 days ago.

Activeupdated 4 months ago

Capability

metadata
{
  "author": "redis",
  "version": "1.0.0"
}

Topics

  • Python
  • TypeScript
  • redis
  • agent-memory
  • session-memory
  • long-term-memory
  • semantic-search
  • redis-cloud

README badge

README badge for redis/agent-skills/iris-development

What it does

Manages session and long-term memory for AI agents on Redis Cloud using the official `redis-agent-memory` (Python) and `@redis-iris/agent-memory` (TypeScript) SDKs. Covers recording conversation events, searching semantically indexed memories, configuring memory stores, and tuning background memory promotion between session and persistent tiers.

Generated from the current SKILL.md.

Frequently asked

Does this skill work with both Python and TypeScript?
Yes. The skill provides code examples for both the official `redis-agent-memory` (Python) SDK and `@redis-iris/agent-memory` (TypeScript) SDK.
What is Redis Agent Memory (RAM)?
It is a managed persistent memory service for AI agents on Redis Cloud with two tiers: session memory for conversation history and long-term memory for semantically searchable facts. A background promotion worker extracts durable facts from sessions automatically.
Do I need to set up a Redis Cloud service first?
Yes. You must create a Memory service on Redis Cloud and obtain an API key and store ID, which the SDK reads from `AGENT_MEMORY_API_KEY` and `AGENT_MEMORY_STORE_ID` environment variables.
Can I search memories semantically?
Yes. The skill covers semantic search of long-term memory with filtering using the `search_long_term_memory()` (Python) or `searchLongTermMemory()` (TypeScript) method.
What is the difference between session events and long-term memory?
Session memory is append-only conversation history per session. Long-term memory stores semantically searchable records extracted from sessions by the background promotion worker or created directly; use the skill's session-when-to-use rule to decide which to use.

Generated from the current SKILL.md. These answers refresh after source changes.