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Everything your AI needs, in one place.
Ready-made agents, skills, personas, prompts, templates and tools. Each one is checked before it goes live, works with any model, and installs in a click. Rate what you use so the best rises to the top.
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A service that does a whole job for you - research, coding, support - and reports back.
Step-by-step instructions an AI follows for one kind of task. Install once, reuse everywhere.
A voice and set of rules layered onto any model: tone, audience, do's and don'ts.
A ready-to-use prompt with fill-in-the-blank variables and notes on when it works best.
A complete routing setup - models, rules and settings - in one file you can apply in a minute.
A single function an AI can call: a calculator, a search, a database lookup.
A language model endpoint with its price, speed and quality declared so the router can compare it.
swarm-advanced
Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
qdrant-vector-search
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable
cupynumeric-parallel-data-load
Load a sharded, on-disk dataset (sharded .npy, Parquet/Arrow, raw binary, sharded HDF5, custom layouts) into a distributed cuPyNumeric ndarray via a manual partition + leaf @task launch with CPU/OMP/G
dsql
Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, mul
qdrant-vector-search
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable
kafka-development-practices
Applies general coding standards and best practices for Kafka development with Scala.
system-design
Scalability, availability, and distributed systems design
swarm-advanced
Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
swarm-advanced
Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
apache-spark
Process large-scale data with Apache Spark. Use when a user asks to process big data, run distributed computations, build ETL pipelines, perform data analysis at scale, or use PySpark for data enginee
elixir
You are an expert in Elixir, the functional programming language built on the Erlang VM (BEAM). You help developers build highly concurrent, fault-tolerant, and distributed systems using Elixir's proc
locust
When the user wants to perform load testing using Python with Locust's distributed architecture and real-time web UI. Also use when the user mentions "locust," "Python load testing," "distributed load
nats-messaging
Build distributed messaging systems with NATS — pub/sub, request/reply, JetStream persistent messaging, and key-value store. Use when someone asks to "set up message queue", "pub/sub system", "event-d
restate
Build resilient distributed applications with Restate — durable execution engine for TypeScript/Java/Go. Use when someone asks to "durable execution", "Restate", "resilient workflows", "distributed tr
temporal
Build reliable distributed workflows with Temporal. Use when a user asks to orchestrate microservices, handle long-running workflows, implement saga patterns, build reliable background jobs, or create
qdrant-vector-search
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable
qdrant-vector-search
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable
qdrant-vector-search
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable
Find
Search or browse by kind. Every card shows who made it, how many people installed it and what they think.
Install
One click. You get a manifest the router understands, plus copy-paste snippets for the CLI, Python and YAML.
Rate and publish
Leave a star rating after you have used it. Made something useful? Publish it - free listings go live immediately.
Prefer the terminal? osr stack apply registry://starter installs the starter template.