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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.
langchain-otel-observability
Wire LangChain 1.0 / LangGraph 1.0 traces into an OpenTelemetry-native backend (Jaeger, Honeycomb, Grafana Tempo, Datadog) with LLM-specific SLOs, safe prompt-content policy, and subgraph-aware span p
langchain-performance-tuning
Tune LangChain 1.0 / LangGraph 1.0 Python chains and agents for throughput, latency, and cost — streaming modes, explicit batch concurrency, semantic plus exact caches, persistent message history, and
langchain-prompt-engineering
Manage LangChain 1.0 prompts like code — LangSmith prompt hub versioning, XML-tag conventions for Claude, few-shot example selection, discriminated-union extraction schemas, and A/B test wiring. Use w
langchain-rate-limits
Rate-limit LangChain 1.0 calls correctly across multi-worker deployments — Redis-backed limiters, asyncio.Semaphore, narrow exception whitelists, and provider-specific throttle handling. Use when hitt
langchain-reference-architecture
A reference layered architecture for production LangChain 1.0 / LangGraph 1.0 services — LLM factory with version-safe defaults, chain/graph registry, retriever and tool DI, Pydantic-validated config,
langchain-sdk-patterns
Compose LangChain 1.0 Python runnables with the production defaults the docs do not warn about: parallel batching, narrow fallbacks, and brace-safe prompts. Use when building an LCEL chain with Runnab
langchain-security-basics
Harden a LangChain 1.0 chain or LangGraph agent against prompt injection, tool abuse, PII leakage in traces, and secrets exfiltration — wrap user content in XML tags, enforce the tool allowlist via pr
langchain-upgrade-migration
Migrate a LangChain 0.3.x Python codebase to LangChain 1.0 / LangGraph 1.0 without breaking production — named breaking changes, codemod patterns, and a phased rollout. Use when upgrading LangChain or
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
posthog-sdk-patterns
Production-ready PostHog SDK patterns: singleton client, typed events, React hooks, Next.js App Router integration, and Python patterns. Trigger: "posthog SDK patterns", "posthog best practices", "pos
replit-sdk-patterns
Apply production-ready patterns for Replit Database, Object Storage, and Auth APIs. Use when implementing Replit integrations, structuring data access layers, or establishing team coding standards for
supabase-sdk-patterns
Use when implementing Supabase queries, auth, realtime, storage, or RPC calls with @supabase/supabase-js or supabase-py and you need production-ready, type-safe patterns that always check the { data,
twinmind-sdk-patterns
Apply production-ready TwinMind SDK patterns for TypeScript and Python. Use when implementing TwinMind integrations, refactoring API usage, or establishing team coding standards for meeting AI integra
auditing-python-dependencies
Audit a Python project's installed dependencies for known CVEs by wrapping pip-audit (PyPA's official vulnerability auditor) and emitting findings in the canonical penetration-tester schema. Detects v
auditing-python-dependencies
Audit a Python project's installed dependencies for known CVEs by wrapping pip-audit (PyPA's official vulnerability auditor) and emitting findings in the canonical penetration-tester schema. Detects v
clade-sdk-patterns
Production-ready Anthropic SDK patterns — client config, retries, timeouts, Use when working with sdk-patterns patterns. error handling, TypeScript types, and async patterns. Trigger with "anthropic s
clay-sdk-patterns
Apply production-ready patterns for integrating with Clay via webhooks and HTTP API. Use when building Clay integrations, implementing webhook handlers, or establishing team coding standards for Clay
deepgram-sdk-patterns
Apply production-ready Deepgram SDK patterns for TypeScript and Python. Use when implementing Deepgram integrations, refactoring SDK usage, or establishing team coding standards for Deepgram. Trigger:
documenso-sdk-patterns
Apply production-ready Documenso SDK patterns for TypeScript and Python. Use when implementing Documenso integrations, refactoring SDK usage, or establishing team coding standards for Documenso. Trigg
firecrawl-sdk-patterns
Apply production-ready Firecrawl SDK patterns for TypeScript and Python. Use when implementing Firecrawl integrations, building reusable scraping services, or establishing team coding standards for Fi
fireflies-sdk-patterns
Apply production-ready Fireflies.ai GraphQL client patterns for TypeScript and Python. Use when implementing Fireflies.ai integrations, building typed clients, or establishing team coding standards fo
genkit-production-expert
Build production Firebase Genkit applications including RAG systems, multi-step flows, and tool calling for Node.js/Python/Go. Deploy to Firebase Functions or Cloud Run with AI monitoring. Use when as
groq-sdk-patterns
Apply production-ready Groq SDK patterns for TypeScript and Python. Use when implementing Groq integrations, refactoring SDK usage, or establishing team coding standards for Groq. Trigger with phrases
ideogram-sdk-patterns
Apply production-ready Ideogram API patterns for TypeScript and Python. Use when implementing Ideogram integrations, refactoring API usage, or establishing team coding standards for Ideogram. Trigger
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Install
One click. You get a manifest the router understands, plus copy-paste snippets for the CLI, Python and YAML.
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Prefer the terminal? osr stack apply registry://starter installs the starter template.