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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.
klingai-webhook-config
Configure webhook callbacks for Kling AI task completion. Use when building event-driven pipelines or replacing polling. Trigger with phrases like 'klingai webhook', 'kling ai callback', 'klingai noti
langchain-observability
Wire LangSmith tracing and custom metric callbacks into a LangChain 1.0 chain or LangGraph 1.0 agent correctly — env-var spelling, subgraph propagation, per-tenant dimensions, cost and latency counter
langchain-webhooks-events
Dispatch LangChain 1.0 chain/agent events to external systems — webhooks, Kafka, Redis Streams, SNS — via async fire-and-forget callbacks, subgraph-aware wiring, and HMAC-signed delivery with idempote
klingai-webhook-config
Configure webhook callbacks for Kling AI task completion. Use when building event-driven pipelines or replacing polling. Trigger with phrases like 'klingai webhook', 'kling ai callback', 'klingai noti
langchain-observability
Wire LangSmith tracing and custom metric callbacks into a LangChain 1.0 chain or LangGraph 1.0 agent correctly — env-var spelling, subgraph propagation, per-tenant dimensions, cost and latency counter
langchain-webhooks-events
Dispatch LangChain 1.0 chain/agent events to external systems — webhooks, Kafka, Redis Streams, SNS — via async fire-and-forget callbacks, subgraph-aware wiring, and HMAC-signed delivery with idempote
pytorch-lightning
High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use
pytorch-lightning
High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use
pytorch-lightning
High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use
dash
Build production-grade interactive dashboards with Plotly Dash - enterprise features, callbacks, and scalable deployment
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.