iris-development
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.
What this skill does
# 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](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) - [`setup-cloud-service`](references/setup-cloud-service.md) - Create a Memory service on Redis Cloud - [`setup-auth-token`](references/setup-auth-token.md) - Authenticate the SDK with a store API key ### 2. Session Memory / Events (HIGH) - [`session-when-to-use`](references/session-when-to-use.md) - Choose session events vs direct long-term memory - [`session-add-event`](references/session-add-event.md) - Append a session event correctly - [`session-retrieval`](references/session-retrieval.md) - Retrieve session memory and individual events ### 3. Long-Term Memory (HIGH) - [`ltm-bulk-create`](references/ltm-bulk-create.md) - Create long-term memories in bulk with idempotent IDs - [`ltm-search`](references/ltm-search.md) - Search long-term memory semantically with filters - [`ltm-organize`](references/ltm-organize.md) - Organize records with namespace, ownerId, topics, and memoryType ### 4. Memory Promotion (MEDIUM) - [`promotion-overview`](references/promotion-overview.md) - How background promotion works ## 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
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.