Workflow-first management for AI agent skills. Group, project, and sync skills across multiple agents with explicit state tracking.
Alexa Skill Flow Builder Framework (SFB-f) core module. Enables and aids importing and creating interactive story skills for Alexa.
Alexa Skill Flow Builder Framework (SFB-F) story debugger. Can run terminal runtime test with StoryMetadata imported by sfb-f core module.
Multi-step workflow orchestration plugin for Clawdbot
Allow parsing of the flow syntax
Strip flow type annotations from your output code.
A JavaScript parser built from the Hermes engine
Tlon/Urbit skill for OpenClaw agents
Skillflag producer CLI reference implementation.
JavaScript parser written in OCaml. Produces ESTree AST
The open agent skills ecosystem
Babel transform for Flow Enums.
Babel preset for all Flow plugins.
Flow types for the Flow-ESTree spec produced by the hermes parser
The Gateway provider for the [AI SDK](https://ai-sdk.dev/docs) allows the use of a wide variety of AI models and providers.
Runtime to be use with the Flow Enums transform.
Lightweight declarative animations powered by platform APIs
A fully-featured caching GraphQL client.
AI SDK by Vercel - build apps like ChatGPT, Claude, Gemini, and more with a single interface for any model using the Vercel AI Gateway or go direct to OpenAI, Anthropic, Google, or any other model provider.
Octokit authentication strategy for OAuth clients
The **[Anthropic provider](https://ai-sdk.dev/providers/ai-sdk-providers/anthropic)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for the [Anthropic Messages API](https://docs.anthropic.com/claude/reference/messages_post).
Flow types for the Javascript AST
All Maestro workflow commands as a single Claude Code skill — intent routing, decision gates, minimal closed-loop chains
The **[OpenAI provider](https://ai-sdk.dev/providers/ai-sdk-providers/openai)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for the OpenAI chat and completion APIs and embedding model support for the OpenAI embeddings API.
Detects and manages psychological flow states based on challenge-skill balance
pikuri-vectordb gives a pikuri-core agent a +vectordb_search+ tool over a local document corpus — agentic search, the agent decides when to retrieve. Ships a swappable backend (a pure-Ruby +Backend::InMemory+ for teaching and a thin +Backend::Chroma+ HTTP client for persistence), a chunker, an embedder wrapper over +RubyLLM.embed+, and an optional +Reranker::LlamaServer+ that speaks +/v1/rerank+ against a cross-encoder model. Text extraction goes through +Pikuri::FileType.read_as_text+ in pikuri-core, which handles plain text / Markdown / PDF; HTML extraction is a deferred follow-up. Hosts wire the feature via +c.add_extension Pikuri::VectorDb::Extension.new(...)+ inside the +Agent.new+ block — same opt-in shape as +pikuri-tasks+ / +pikuri-skills+. The bundled +Pikuri::VectorDb::LIBRARIAN+ persona is the privilege-separated sub-agent counterpart for hosts that want recall to flow through a child rather than the parent's context. Three model endpoints in the full setup — chat (via ruby_llm), an embedder (via +RubyLLM.embed+), and an optional reranker (HTTP +/v1/rerank+). A single +llama-server+ in router mode serves all three by default, loading each cached GGUF on demand; see the gem's README for details.
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