Repository classification
Standalone decision-model library and services; supplied files document no Claude Code plugin, skill, hook, command, or installation path.
README.mdLocal decision-model SDK and MCP tool server · Active versioned project with documented release 0.3.21, multiple runtime surfaces, examples, tests, and research harnesses; repository dates in 2026 remain externally unreconciled.
Apache-2.0 multilingual decision-model toolkit that provides Python and TypeScript SDKs, local CLI and HTTP serving, ONNX runtimes, framework integrations, evaluation harnesses, and an optional MCP server for fast typed choice, ordinal-score, and yes/no decisions; no native Claude Code plugin, hook, skill, or Claude-specific installation path is evidenced.
Selection
Boundaries
Strengths
Risk profile
The supplied documentation describes optional bearer authentication for prediction endpoints, configurable checkpoint revisions and SHA-256 maps, request validation and option-count guards, a hardened DynamicUser NixOS service, and hook timeouts or error policy. It also states that the server binds to 0.0.0.0 by default, leaves TLS and CORS to a proxy, and keeps /health public. Hooks can rewrite inputs or outputs, skip inference, and forward data externally, so hook code is trusted. The MCP implementation and its authentication or authorization controls were not supplied. No independent audit or complete threat model was provided.
Component inventory
Standalone decision-model library and services; supplied files document no Claude Code plugin, skill, hook, command, or installation path.
README.mdLoads checkpoints and makes typed choice, score, and yes/no decisions over text or structured state.
README.mdDetects language/script, selects a checkpoint, manages loaded models, and supports routed prediction batches.
README.mdProjects JSON Schema or Pydantic object properties into typed Laya questions and schema-shaped results.
docs/structured.mdRoutes or predicts local decisions interactively, from one input, custom questions, presets, stdin, or batch files.
README.mdValidates labelled JSONL, evaluates checkpoints, slices metrics, and fails on configured quality regressions.
research/evals/README.mdSelf-hosted FastAPI inference service exposing Jev-compatible single and batch System One endpoints.
README.mdAccepts typed decision requests and returns model, answers, usage, and optional routing metadata.
sdk/typescript/README.mdOptional MCP extra exposes documented prediction, routed batch, and structured-decision tools.
README.mdObserves or modifies routing and inference for logging, redaction, caching, metrics, gating, and overrides.
docs/hooks/index.mdSupplies ready-made schemas for triage, email, guardrails, moderation, and model routing.
README.mdProvides router, guardrail, and structured-decision runnables with shared synchronous and asynchronous batching.
docs/langchain.mdRuns exported checkpoints through ONNX Runtime with prediction, batching, long-document, and structured-decision APIs.
README.mdOptionally replaces supported CUDA forward operations with fused TileLang kernels and CUDA graphs.
README.mdRuns Laya inference directly in Node or browsers using split ONNX models, routing, hooks, batching, and structured decisions.
laya-ts/README.mdDependency-free ESM/CommonJS client for a self-hosted laya-serve endpoint, with typed schemas and cancellation.
sdk/typescript/README.mdTwo-pane local GUI for editing requests, running predictions, inspecting distributions, and copying curl or Python.
examples/server.pyRuns a hardened systemd laya-serve unit with model caching, CUDA access, firewall, and credential options.
README.mdMeasures MASSIVE intent accuracy, macro-F1, ECE, confidence, and per-case output for selected languages.
research/eval/laya_eval.pyMeasures option-order and label-renaming stability, probability drift, budget confounding, and selective-prediction signals.
research/eval/metamorphic.pyTechnical profile
Classification
Evidence: Laya runs as its own Python/TypeScript library, CLI, HTTP service, browser runtime, and optional MCP server. Inference: its generic MCP tools could be connected to Claude Code, but no Claude-specific plugin, skill, hook, or setup is documented; model downloads and runtime selection make setup medium.
Runs Alongside · medium setup effort · medium confidence · automatedEvidence and risk
Routing context
No catalog relationships have been documented yet.