schemarouter 0.6.0

Schema-aware planning and execution for LLM tool ecosystems.

English · 한국어 · Docs · Latest release

SchemaRouter sits between an agent and its tools. It turns a natural-language request plus a registered capability catalog into a small, typed execution plan, then validates that plan again at runtime before anything executes.

Query
  -> Tool
  -> Endpoint
  -> Parameters
  -> Response fields
  -> Policy / evidence
  -> Schema validation
  -> Execute

It is not another general agent framework. LangChain, LangGraph, LlamaIndex, or your own orchestrator can stay above it; OpenAPI, MCP, OPTIMADE, Python callables, and adapter plugins stay below it.

Agent / graph / application orchestrator
                 |
           SchemaRouter
     typed planning + validation
                 |
        capability sources
 OpenAPI / MCP / OPTIMADE / Python

Optional decision backends (Laya / Ollama / Jev) plug into SchemaRouter's bounded selection step.
They do not become agents, do not run tool loops, and do not receive execution authority.

Current stable release: 0.6.0 · pip install schemarouter · pre-1.0

Why SchemaRouter

Tool selection alone is not enough once an agent has many capabilities. SchemaRouter makes the execution boundary explicit:

• choose a declared tool and endpoint;
• accept only declared parameters and output fields;
• validate inputs and raw outputs with JSON Schema;
• reject stale schema fingerprints and stale invoker bindings;
• keep mutation/destructive authority local and fail closed;
• separate credentials from model-visible arguments;
• bound retries, elapsed time, remote calls, and response size;
• surface OpenAPI compatibility gaps instead of silently guessing.

Quickstart

from pydantic import BaseModel
from schemarouter import PlanRequest, SchemaRouter, schema_tool


class Weather(BaseModel):
    city: str
    temperature: float


@schema_tool(read_only=True)
def current_weather(city: str) -> Weather:
    return Weather(city=city, temperature=20.5)


router = SchemaRouter()
router.add_callable(current_weather)

result = router.invoke(
    PlanRequest(query="city temperature", arguments={"city": "Seoul"})
)

print(result[0].data)

Connect capabilities

Framework bridges are available for LangChain, LangGraph, and LlamaIndex. OpenTelemetry provides optional telemetry export. Jev / TypeSafe, Laya, and Ollama are optional decision backends, not agent frameworks. Existing GPT, Gemini, Claude, or other hosted model clients can also be injected through the provider-neutral ModelQueryAnalyzer or CallableDecisionBackend contracts. None of these paths bypass SchemaRouter's policy, schema validation, or execution boundary.

What 0.6 adds

0.6 adds optional local/model-assisted decision backends, operational inspection/dashboard surfaces, and a broader fail-closed OpenAPI subset:

• local Laya decisions with CPU/CUDA/MPS device controls and benchmark metadata;
• provider-neutral reuse of existing GPT, Gemini, Claude, or other hosted clients;
• live/persistent inspection plus a self-contained read-only HTML dashboard;
• response oneOf/anyOf field discovery and static same-origin $id/$anchor resolution;
• typed JSON root request bodies, OpenAPI 3.0 nullable normalization, and default parameter-style serialization.

See the 0.6.0 release notes for details.

Inspect what SchemaRouter built

Persisted registries and run traces can be inspected without executing tools:

schemarouter inspect registry --db ./registry.sqlite3
schemarouter inspect tool materials --db ./registry.sqlite3
schemarouter inspect traces --db ./traces.sqlite3
schemarouter inspect trace <RUN_ID> --db ./traces.sqlite3
schemarouter dashboard \
  --registry ./registry.sqlite3 \
  --traces ./traces.sqlite3 \
  --output ./artifacts/schemarouter-dashboard.html

Add --json to inspection commands for automation. The dashboard is a self-contained read-only HTML export built from the same inspection contracts. The registry view exposes tool/endpoint topology, method/path, mutation classification, parameter/output-field counts, and schema fingerprints; trace views expose persisted run/event history.

Operational inspection guide

Documentation

Start with the manual rather than this README:

• Install and quickstart
• Understand the execution model
• OpenAPI guide
• Runtime policy and retry
• Framework integrations
• API reference
• Architecture and maturity
• Security model

Development

python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"

ruff check .
pytest -q -m "not mcp_integration"

The protected CI surface also covers Python 3.10–3.14, Windows, minimum dependencies, package artifacts, Pyright, coverage, documentation, and optional integration suites.

Scope

SchemaRouter intentionally does not implement another chat abstraction, model-provider layer, memory system, checkpoint store, or graph runtime.

Natural-language request → typed tool execution plan → validated execution.

Research and license

SchemaRouter originated from SchemaRouter: Field-Aware Tool Routing for Efficient Heterogeneous Agentic RAG.

MIT © 2026 Yong-eun Cho