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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.
Ocala Asset Security Agent API
x402-native market evidence, data refinement, and government solicitation extraction for autonomous agents.
bulletmind
Convert input into clean, structured, hierarchical bullet points for summarization, note-taking, and structured thinking.
pydantic-ai
Build production-ready AI agents with PydanticAI — type-safe tool use, structured outputs, dependency injection, and multi-model support.
llm-engineering-expert
Build reliable applications on large language models: prompt design, structured output, evaluation, guardrails, and cost and latency control. Use when the user mentions LLMs, prompts, prompt engineeri
guidance
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained genera
instructor
Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-te
pydantic-ai
Build production-ready AI agents with PydanticAI — type-safe tool use, structured outputs, dependency injection, and multi-model support.
guidance
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained genera
instructor
Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-te
llm-structured-output
Design prompts, schemas, validation, and recovery logic for reliable machine-readable model outputs. Use when generating JSON, typed objects, extraction results, tool arguments, or any output another
guidance
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained genera
instructor
Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-te
pydantic-ai
Build typed LLM applications with PydanticAI: schema-constrained outputs, tool integration, validation, retries, and deterministic downstream handoffs. Use when users need reliable structured outputs
guidance
You are an expert in Guidance, Microsoft's library for controlling LLM output with constrained generation. You help developers write programs that interleave text generation with control flow (loops,
instructor
You are an expert in Instructor, the library for getting structured, validated output from LLMs. You help developers extract typed data from unstructured text using Pydantic models (Python) or Zod sch
pydantic-ai
You are an expert in PydanticAI, the Python agent framework built by the Pydantic team. You help developers create type-safe AI agents with structured outputs, dependency injection, tool definitions,
bulletmind
Convert input into clean, structured, hierarchical bullet points for summarization, note-taking, and structured thinking.
bulletmind
Convert input into clean, structured, hierarchical bullet points for summarization, note-taking, and structured thinking.
bulletmind
Convert input into clean, structured, hierarchical bullet points for summarization, note-taking, and structured thinking.
bulletmind
Convert input into clean, structured, hierarchical bullet points for summarization, note-taking, and structured thinking.
bulletmind
Convert input into clean, structured, hierarchical bullet points for summarization, note-taking, and structured thinking.
bulletmind
Convert input into clean, structured, hierarchical bullet points for summarization, note-taking, and structured thinking.
pydantic-ai
Build production-ready AI agents with PydanticAI — type-safe tool use, structured outputs, dependency injection, and multi-model support.
pydantic-ai
Build production-ready AI agents with PydanticAI — type-safe tool use, structured outputs, dependency injection, and multi-model support.
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.