### Run Quickstart Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/examples/typescript/README.md

Command to execute the quickstart TypeScript example using tsx. This requires tsx to be installed or available.

```bash
npx tsx examples/typescript/01-quickstart.ts

```

--------------------------------

### Quick Start Development Setup

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenmatch/CONTRIBUTING.md

Clone the repository, install development dependencies, and run tests to quickly set up your environment for contributing.

```bash
git clone https://github.com/benseverndev-oss/goldenmatch.git
cd goldenmatch
pip install -e "[dev]"
pytest --tb=short
```

--------------------------------

### Install infermap and Navigate to Examples

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/infermap/examples/README.md

Installs the infermap Python package and changes the directory to the examples folder. This is the initial setup step for running the Python examples.

```bash
pip install infermap
cd examples/
```

--------------------------------

### Goldensuite-MCP Quickstart Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/docs/superpowers/specs/2026-05-13-golden-suite-package-audit.md

Example of how to serve the Goldensuite-MCP endpoint.

```python
goldensuite-mcp serve
```

--------------------------------

### Setup and Run Tests

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldencheck/CONTRIBUTING.md

Clone the repository, install development dependencies, and run tests to verify the setup.

```bash
git clone https://github.com/benseverndev-oss/goldencheck.git
cd goldencheck
pip install -e ".[dev]"
pytest
```

--------------------------------

### GoldenPipe Quickstart Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/docs/superpowers/specs/2026-05-13-golden-suite-package-audit.md

Example of how to run the GoldenPipe orchestrator with a customer CSV file.

```python
gp.run("customers.csv")
```

--------------------------------

### Install and Run Python Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenflow/examples/README.md

Installs the goldenflow Python package and executes a zero-configuration transform example.

```bash
pip install goldenflow
python examples/zero_config.py
```

--------------------------------

### Install and Start Local MCP Server

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenmatch/docs/mcp.md

Install the necessary package and start the local MCP server using the command line. Supports CSV files and optional HTTP transport.

```bash
pip install goldenmatch[mcp]
goldenmatch mcp-serve --file customers.csv --config config.yaml
# Or with HTTP transport:
goldenmatch mcp-serve --file customers.csv --transport http --port 8200
```

--------------------------------

### dbt-GoldenCheck Quickstart Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/docs/superpowers/specs/2026-05-13-golden-suite-package-audit.md

Example of how to run dbt dependencies and then execute the GoldenCheck Python runner.

```bash
dbt deps 
run_goldencheck.py
```

--------------------------------

### Infermap Quickstart Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/docs/superpowers/specs/2026-05-13-golden-suite-package-audit.md

Example of how to use the Infermap engine for schema mapping between source and target.

```python
infermap.map(src, tgt)
```

--------------------------------

### Install DQBench for Benchmarking

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenpipe/examples/README.md

Install the DQBench tool, often used for benchmarking GoldenPipe tools. This is a prerequisite for specific benchmarking examples.

```bash
pip install goldenpipe[golden-suite] dqbench
```

--------------------------------

### GoldenFlow Quickstart Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/docs/superpowers/specs/2026-05-13-golden-suite-package-audit.md

Example of how to use GoldenFlow to transform a data CSV file.

```python
goldenflow transform data.csv
```

--------------------------------

### Python Quick Start

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenflow/README.md

Install GoldenFlow, run auto-transform, use demo data, learn a config, or map schemas.

```bash
pip install goldenflow

# Auto-transform (zero-config)
goldenflow transform messy_data.csv

# Try the demo first
goldenflow demo
goldenflow transform demo_data.csv -c demo_config.yaml

# With config
goldenflow learn messy_data.csv -o config.yaml
goldenflow transform messy_data.csv -c config.yaml

# Schema mapping
goldenflow map --source system_a.csv --target system_b.csv

# Full pipeline
goldencheck scan data.csv
goldenflow transform data.csv
goldenmatch dedupe data_transformed.csv
```

--------------------------------

### Quickstart: Deduplicate Record Array

Source: https://github.com/benzsevern/goldenmatch/blob/main/examples/typescript/README.md

A 30-second example demonstrating how to deduplicate an array of records using the goldenmatch library. Ensure 'goldenmatch' is installed.

```typescript
import { goldenmatch } from "goldenmatch";

const records = [
  { id: 1, name: "Alice", age: 30 },
  { id: 2, name: "Bob", age: 25 },
  { id: 1, name: "Alice", age: 30 }, // Duplicate
  { id: 3, name: "Charlie", age: 35 },
  { id: 2, name: "Robert", age: 25 }, // Similar to Bob
];

const deduplicated = goldenmatch(records, {
  // Define keys to consider for matching
  keys: ["id", "name", "age"],
  // Optional: configure scoring thresholds or algorithms
});

console.log(deduplicated);
/*
Output might look like:
[
  { id: 1, name: 'Alice', age: 30 },
  { id: 2, name: 'Bob', age: 25 },
  { id: 3, name: 'Charlie', age: 35 },
  { id: 2, name: 'Robert', age: 25 } // Depending on scoring, might be kept or merged
]
*/

```

--------------------------------

### Initialize GoldenFlow Setup Wizard

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenflow/AGENTS.md

Launches an interactive wizard to guide the user through the initial setup process.

```bash
goldenflow init data.csv
```

--------------------------------

### GoldenCheck Quickstart Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/docs/superpowers/specs/2026-05-13-golden-suite-package-audit.md

Example of how to run GoldenCheck for data validation on a CSV file.

```python
goldencheck data.csv
```

--------------------------------

### Example Prompt for suggest_config Tool

Source: https://github.com/benzsevern/goldenmatch/wiki/MCP-Server

Use this prompt to get suggestions for improving matching thresholds and weights based on bad merges.

```text
"Cluster 5 has a bad merge. What should I change?"
```

--------------------------------

### Quick Start for DuckDB UDFs (Python)

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/rust/extensions/CONTRIBUTING.md

Clone the repository, navigate to the DuckDB directory, install dependencies, and run tests.

```bash
git clone https://github.com/benseverndev-oss/goldenmatch-extensions.git
cd goldenmatch-extensions/duckdb
pip install -e ".[dev]"
pytest --tb=short
```

--------------------------------

### TypeScript/Node.js Quick Start

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenflow/README.md

Install GoldenFlow, run auto-transform, use demo data, learn a config, or map schemas.

```bash
npm install goldenflow

# Auto-transform (zero-config)
npx goldenflow-js transform messy_data.csv

# Try the demo first
npx goldenflow-js demo
npx goldenflow-js transform demo_data.csv -c demo_config.yaml

# With config
npx goldenflow-js learn messy_data.csv -o config.yaml
npx goldenflow-js transform messy_data.csv -c config.yaml

# Schema mapping
npx goldenflow-js map -s system_a.csv -t system_b.csv
```

--------------------------------

### Install goldensuite-mcp and Serve

Source: https://github.com/benzsevern/goldenmatch/wiki/Master-MCP-Aggregator

Install the package using pip and then start the MCP server. The server can be configured to use HTTP transport on a specified port.

```bash
pip install goldensuite-mcp
goldensuite-mcp serve --transport http --port 8300
```

--------------------------------

### Reproduce DQbench Composite Benchmark

Source: https://github.com/benzsevern/goldenmatch/blob/main/docs/reproducing-benchmarks.md

Clones the repository, sets up a virtual environment, installs dependencies, configures environment variables, and runs the DQbench benchmark. This is a comprehensive guide for a clean reproduction.

```bash
# Fresh checkout, fresh venv, no inherited memory cache
git clone https://github.com/benseverndev-oss/goldenmatch
cd goldenmatch
git checkout v1.12.0      # tag where the 91.04 number landed

python -m venv .venv
. .venv/bin/activate       # Windows: .venv\Scripts\activate

pip install -U pip
pip install -e packages/python/goldenmatch
pip install dqbench

export GOLDENMATCH_AUTOCONFIG_MEMORY=0
unset OPENAI_API_KEY                # no-LLM measurement

python scripts/run_benchmarks.py --datasets dqbench \
  --output dqbench_results.json

# Expected: composite >= 90 (target was >= 75; v1.12 shipped at 91.04)
cat dqbench_results.json
```

--------------------------------

### Install Dependencies with Just

Source: https://github.com/benzsevern/goldenmatch/blob/main/docs/superpowers/plans/2026-05-01-goldenmatch-monorepo-fold-in.md

Executes the 'install' command defined in the Justfile to install all project dependencies.

```bash
just install
```

--------------------------------

### Web Workbench Installation and Serving

Source: https://github.com/benzsevern/goldenmatch/blob/main/README.md

Install the web UI extra for GoldenMatch and start the local development server. This allows for browser-based editing of rules, labeling pairs, and comparing runs.

```bash
pip install 'goldenmatch[web]'
goldenmatch serve-ui my-project   # opens http://localhost:5050
```

--------------------------------

### Python Quickstart for Identity Graph

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenpipe/docs/identity-graph.md

Enable the identity graph stage in Python by passing identity options to the `gp.run` function. This example also prints the identity summary artifact.

```python
import goldenpipe as gp

result = gp.run(
    "customers.csv",
    identity_opts={
        "path": ".goldenmatch/identity.db",
        "source_pk_column": "customer_id",
        "dataset": "customers",
    },
)
print(result.artifacts["identity_summary"])
# {'created': 12, 'absorbed_records': 0, 'merged': 0, 'split': 0,
#  'edges_added': 27, 'events_emitted': 12, 'records_upserted': 100,
#  'conflicts_flagged': 0}
```

--------------------------------

### Simulated Single-Node Ray Cluster Setup and Benchmarking

Source: https://github.com/benzsevern/goldenmatch/blob/main/docs/distributed-ray-cluster-setup.md

Starts a head node and three workers for CI and code-path validation. Runs the cluster-agnostic Phase 5 benchmark and then tears down the cluster. Includes honest scoping caveats for single NIC, single disk, and shared page cache.

```bash
# Start head + 3 workers, each with 4 CPU and 8 GB object store.
ray start --head --port=6379 --num-cpus=4 \
  --object-store-memory=8000000000 --dashboard-host=127.0.0.1
for i in 1 2 3;
  ray start --address=127.0.0.1:6379 --num-cpus=4 \
    --object-store-memory=8000000000
done
ray status  # confirm 4 nodes, 16 CPU total

# Run the cluster-agnostic Phase 5 bench.
RAY_ADDRESS=127.0.0.1:6379 \
GOLDENMATCH_DISTRIBUTED_PIPELINE=2 \
GOLDENMATCH_ENABLE_DISTRIBUTED_RAY=1 \
python scripts/bench_phase5_simulated.py \
  --parquet bench-dataset/bench_50000000.parquet \
  --rows 50000000 \
  --identity false \
  --out bench_phase5_simulated.json

# Tear down.
ray stop --force
```

--------------------------------

### Development Setup

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldencheck/docs/installation.md

Clone the repository and install GoldenCheck in editable mode with development and all optional dependencies.

```bash
git clone https://github.com/benseverndev-oss/goldencheck.git
cd goldencheck
pip install -e ".[dev,llm,mcp,baseline,semantic]"
```

--------------------------------

### Install and Run GoldenCheck

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldencheck/docs/index.md

Installs the GoldenCheck package and runs a basic scan on a CSV file. This is the quickest way to get started.

```bash
pip install goldencheck
goldencheck data.csv
```

--------------------------------

### Install Infermap Dependencies (Bash)

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/infermap/examples/typescript/README.md

Install necessary dependencies and link the infermap package locally. This setup is required before running the TypeScript examples.

```bash
cd packages/infermap-js
npm install
npm run build
npm link                       # makes `infermap` resolvable from anywhere
cd ../..
npm install --no-save tsx      # runner for TypeScript
```

--------------------------------

### Install and Check Version

Source: https://github.com/benzsevern/goldenmatch/wiki/CLI-Reference

Install the GoldenMatch package and verify the installation by checking the version.

```bash
pip install goldenmatch
goldenmatch --version
```

--------------------------------

### Run GoldenMatch Setup Wizard

Source: https://github.com/benzsevern/goldenmatch/wiki/Interactive-TUI

Execute the setup wizard for first-time users to configure GPU mode, API keys, and database settings.

```bash
goldenmatch setup
```

--------------------------------

### Local MCP Server Setup (Bash)

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenflow/README.md

Installs the necessary package for the local MCP server and starts it. This is for running GoldenFlow's MCP services on your own machine.

```bash
pip install goldenflow[mcp]
goldenflow mcp-serve
```

--------------------------------

### Quick Start with GoldenCheck in TypeScript

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldencheck/docs/typescript.md

A basic example demonstrating how to import and use GoldenCheck to scan tabular data and log any findings. Ensure you have the 'goldencheck' package installed.

```typescript
import { scanData, TabularData } from "goldencheck";

const data = new TabularData([
  { id: 1, email: "alice@example.com", age: 30 },
  { id: 2, email: "not-an-email", age: -5 },
]);

const { findings } = scanData(data);
findings.forEach(f => console.log(`[${f.check}] ${f.column}: ${f.message}`));
```

--------------------------------

### CLI Command: Interactive Setup

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenflow/docs/llms-full.txt

Launches an interactive setup process for a data file.

```bash
goldenflow init data.csv                           # Interactive setup
```

--------------------------------

### Install and Run TypeScript Examples

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenflow/examples/README.md

Installs the goldenflow npm package and executes various TypeScript examples using tsx.

```bash
npm install goldenflow
npx tsx examples/typescript/zero-config.ts
```

```bash
npx tsx examples/typescript/configured-transform.ts
```

```bash
npx tsx examples/typescript/schema-mapping.ts
```

```bash
npx tsx examples/typescript/streaming.ts
```

```bash
npx tsx examples/typescript/profiling.ts
```

```bash
npx tsx examples/typescript/edge-safe.ts
```

--------------------------------

### Run GoldenMatch Demo and Setup

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenmatch/docs/wiki/Home.md

Execute the built-in demo to see GoldenMatch in action, or run the interactive setup wizard to configure the tool.

```bash
goldenmatch demo
goldenmatch setup
```

--------------------------------

### `ray up` Configuration Example for GCP

Source: https://github.com/benzsevern/goldenmatch/blob/main/docs/distributed-ray-cluster-setup.md

Defines a Ray cluster configuration for GCP, specifying node types, counts, and setup commands for installing Python packages and increasing shared-memory size for Ray's object store.

```yaml
# ray-cluster.yaml
cluster_name: goldenmatch-phase5

provider:
  type: gcp  # or aws, azure, kubernetes
  region: us-central1
  project_id: your-project

head_node_type: head
worker_node_types:
  head:
    node_config:
      machineType: n2-standard-4
    resources: {"CPU": 4}
    min_workers: 0
    max_workers: 0
  worker:
    node_config:
      machineType: n2-standard-16
    resources: {"CPU": 16}
    min_workers: 4
    max_workers: 4

# Pin python + packages to match the goldenmatch dev image.
setup_commands:
  - pip install "goldenmatch[ray]==1.16.0"
  - pip install psutil pandas scipy

# Increase shared-memory size for Ray's object store.
# Default 30% is too low for the shuffle stages at 100M.
file_mounts: {}
```

--------------------------------

### Manual Installation from Pre-built Binaries

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/rust/extensions/README.md

Extract the downloaded `.tar.gz` archive and copy the extension files to the appropriate PostgreSQL directories using `pg_config`.

```bash
tar xzf goldenmatch_pg-v0.2.0-pg16-py312-linux-x86_64.tar.gz
sudo cp goldenmatch_pg-v0.2.0-pg16-py312-linux-x86_64/*.so $(pg_config --pkglibdir)/
sudo cp goldenmatch_pg-v0.2.0-pg16-py312-linux-x86_64/*.control $(pg_config --sharedir)/extension/
sudo cp goldenmatch_pg-v0.2.0-pg16-py312-linux-x86_64/*.sql $(pg_config --sharedir)/extension/
```

--------------------------------

### Learn and Reuse Configuration Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenflow/docs/llms-full.txt

Learn a transformation configuration from a sample CSV file and save it to a YAML file for later use.

```python
import goldenflow as gf
config = gf.learn_config("sample.csv")
gf.save_config(config, "goldenflow.yaml")
```

--------------------------------

### YAML Configuration for Predefined Plugins

Source: https://github.com/benzsevern/goldenmatch/blob/main/docs/superpowers/specs/2026-05-22-predefined-merge-plugins-design.md

Illustrates how to opt into predefined plugins using YAML configuration. Shows examples for numeric_max, email_normalize, system_of_record, and freshness_with_max_age strategies, including custom rule arguments.

```yaml
golden_rules:
  field_rules:
    lifetime_value:
      strategy: "custom:numeric_max"
    email:
      strategy: "custom:email_normalize"
    crm_status:
      strategy: "custom:system_of_record"
      source_priority: ["salesforce", "hubspot"]
    last_seen_at:
      strategy: "custom:freshness_with_max_age"
      date_column: "last_seen_at"
```

--------------------------------

### Install and Run GoldenMatch

Source: https://github.com/benzsevern/goldenmatch/wiki/Home

Install the GoldenMatch package using pip and run the demo or setup wizard.

```bash
pip install goldenmatch
goldenmatch demo
goldenmatch setup
```

--------------------------------

### Configuration Example (pipeline.yaml)

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenpipe/docs/llms-full.txt

A sample `pipeline.yaml` file demonstrating stage definitions, conditional routing with `severity_gate`, and fuzzy matching parameters.

```yaml
stages:
  - name: check
    enabled: true

  - name: flow
    enabled: true
    decision: severity_gate
    params:
      max_errors: 0

  - name: match
    enabled: true
    params:
      fuzzy:
        name: 0.85
        address: 0.80
```

--------------------------------

### Install GoldenPipe with Golden Suite

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenpipe/examples/README.md

Install the GoldenPipe package with the golden-suite extra for full functionality. This is a prerequisite for most examples.

```bash
pip install goldenpipe[golden-suite]
```

--------------------------------

### CLI Command: Demo

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenflow/docs/llms-full.txt

Generates sample data for demonstration purposes.

```bash
goldenflow demo                                    # Generate sample data
```

--------------------------------

### Run GoldenMatch Example Locally

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/typescript/goldenmatch/examples/README.md

Provides instructions for running a specific GoldenMatch TypeScript example, '01-basic-dedupe.ts', after installing project dependencies. This is a common way to test examples locally.

```bash
cd packages/goldenmatch-js
npm install
npx tsx examples/01-basic-dedupe.ts
```

--------------------------------

### Run GoldenMatch Interactive Setup Wizard

Source: https://github.com/benzsevern/goldenmatch/blob/main/README.md

Execute the interactive wizard for GoldenMatch setup, which configures GPU, API keys, and databases.

```bash
goldenmatch setup    # interactive wizard: GPU, API keys, database
```

--------------------------------

### Install and Run Basic Deduplication

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenmatch/examples/README.md

Installs the goldenmatch library and runs a basic deduplication script. This is a starting point for using the library.

```bash
pip install goldenmatch
cd examples
python basic_dedupe.py
```

--------------------------------

### Run GoldenMatch Example Globally

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/typescript/goldenmatch/examples/README.md

Illustrates how to run a GoldenMatch TypeScript example, '01-basic-dedupe.ts', after installing 'tsx' globally. This method is useful for running examples without needing to navigate into the project directory.

```bash
npm install -g tsx
tsx examples/01-basic-dedupe.ts
```

--------------------------------

### Run MCP Client Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/examples/typescript/README.md

Command to execute the MCP client TypeScript example using tsx. This requires tsx and the '@modelcontextprotocol/sdk' to be installed.

```bash
npx tsx examples/typescript/03-mcp-client.ts

```

--------------------------------

### Install and Run Python Benchmark

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/infermap/docs/benchmark.md

Installs the necessary Python development dependencies and runs the infermap benchmark, outputting results to a JSON file. Also shows how to generate a human-readable report.

```bash
pip install -e ".[dev]"
pip install -e "benchmark/runners/python[dev]"
python -m infermap_bench run --output report-py.json
python -m infermap_bench report report-py.json
```

--------------------------------

### Development Setup for GoldenCheck

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldencheck/docs/wiki/Installation.md

Clones the GoldenCheck repository and installs it in editable mode with development and all optional dependencies. This setup is suitable for contributing to the project.

```bash
git clone https://github.com/benseverndev-oss/goldencheck.git
cd goldencheck
pip install -e ".[dev,llm,mcp]"
```

--------------------------------

### Install and Run A2A Server

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenmatch/docs/agent.md

Install the necessary package and start the A2A server on a specified port. Other agents can then discover GoldenMatch at the /.well-known/agent.json endpoint.

```bash
pip install goldenmatch[agent]
goldenmatch agent-serve --port 8200
```

--------------------------------

### Discovery and History Commands

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenflow/README.md

Commands for initializing setup, generating demos, and viewing transform run history.

```bash
goldenflow init data.csv                         # Interactive setup wizard
```

```bash
goldenflow demo                                  # Generate sample data to try
```

```bash
goldenflow history                               # Show recent transform runs
```

```bash
goldenflow history -n 50                         # Last 50 runs
```

--------------------------------

### Run TypeScript Example with tsx (Bash)

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/infermap/examples/typescript/README.md

Alternatively, run examples from within a project that already has infermap installed. This command uses `tsx` to execute the TypeScript file.

```bash
npm install infermap tsx
npx tsx path/to/example.ts
```

--------------------------------

### Start Local GoldenPipe MCP Server

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenpipe/README.md

Installs the necessary components for running a local GoldenPipe MCP server and then starts the server. This allows local connections to the GoldenPipe service.

```bash
pip install goldenpipe[mcp]
goldenpipe mcp-serve
```

--------------------------------

### Example Prompt for pprl_auto_config Tool

Source: https://github.com/benzsevern/goldenmatch/wiki/MCP-Server

Use this prompt to analyze data and receive recommendations for optimal PPRL parameters.

```text
"What PPRL settings should I use for this dataset?"
```

--------------------------------

### Run Suite Container Images

Source: https://github.com/benzsevern/goldenmatch/wiki/Containers

Examples for running Suite container images. Use the first command for a single container with all tools, or subsequent commands for per-package deployments. The last example shows how to run the Postgres extension container.

```bash
# One container, every Suite tool
docker run -p 8300:8300 ghcr.io/benzsevern/goldensuite-mcp:latest

# Per-package containers — narrower deployments
docker run -p 8200:8200 ghcr.io/benzsevern/goldenmatch-mcp:latest

# Postgres + extension preinstalled
docker run -e POSTGRES_PASSWORD=secret -p 5432:5432 \
    ghcr.io/benzsevern/goldenmatch-extensions:latest
```

--------------------------------

### Install Optional Peer Dependency for YAML

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/typescript/goldenmatch/examples/README.md

Shows how to install the 'yaml' package, which is an optional peer dependency required for examples that involve saving or loading GoldenMatch configurations in YAML format.

```bash
npm install yaml
```

--------------------------------

### Quick Start for Postgres Extension (Rust)

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/rust/extensions/CONTRIBUTING.md

Navigate to the Postgres directory and run tests or the pgrx run command. Requires Rust toolchain, LLVM/libclang, and PostgreSQL dev headers. Local Windows builds are not supported.

```bash
cd postgres
cargo test        # Linux/CI only
cargo pgrx run    # Linux/CI only
```

--------------------------------

### Install and Deduplicate CSV with GoldenMatch

Source: https://github.com/benzsevern/goldenmatch/blob/main/README.md

Installs the goldenmatch package and demonstrates its basic usage for deduplicating a CSV file. This is a quick way to start using the tool for common deduplication tasks.

```bash
pip install goldenmatch && goldenmatch dedupe customers.csv
```

--------------------------------

### Interactive Configuration Wizard

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenmatch/docs/cli.md

Use `goldenmatch init` to start an interactive wizard for creating or initializing configuration files.

```bash
goldenmatch init
```

--------------------------------

### Full GitHub Action Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldencheck/docs/github-action.md

A comprehensive example of a GitHub Actions workflow that includes GoldenCheck for data quality. This setup checks pull requests, checks out code, runs GoldenCheck with specific configurations, and sets a failure threshold.

```yaml
name: Data Quality
on: [pull_request]

jobs:
  check:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: benseverndev-oss/goldencheck-action@v1
        with:
          files: "data/*.csv"
          fail-on: error
          config: goldencheck.yml
```

--------------------------------

### Software Pack Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenmatch/docs/domain-packs.md

Demonstrates the extraction of name, version, edition, and platform from a software product title.

```text
"Microsoft Office 365 Professional Plus - Windows"
  -> name: Microsoft Office
  -> version: 365
  -> edition: Professional Plus
  -> platform: Windows
```

--------------------------------

### Database Synchronization - Initial Run

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenmatch/README.md

Perform an initial full scan for database synchronization, creating necessary metadata tables.

```bash
# First run: full scan, create metadata tables
goldenmatch sync --table customers --connection-string "$DATABASE_URL" --config config.yaml
```

--------------------------------

### Example Prompt for create_domain Tool

Source: https://github.com/benzsevern/goldenmatch/wiki/MCP-Server

Use this prompt to create a new custom domain pack with specified fields.

```text
"Create a domain pack for automotive parts with fields: part_number, manufacturer, fitment"
```

--------------------------------

### Remote GPU Endpoint: Server Setup

Source: https://github.com/benzsevern/goldenmatch/wiki/GPU-Routing

Installs the sentence-transformers library and runs the GPU endpoint script on the machine with the GPU.

```bash
pip install sentence-transformers
python scripts/gpu_endpoint.py --port 8090
```

--------------------------------

### Install Dependencies and Run Tests

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/infermap/docs/superpowers/plans/2026-03-29-infermap-implementation.md

Command to install the project in editable mode with development dependencies and run tests.

```bash
cd D:/show_case/infermap && pip install -e ".[dev]" && pytest tests/test_types.py -v
```

--------------------------------

### Launch Goldenmatch Interactive TUI

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenmatch/docs/typescript.md

Start the interactive Text User Interface for Goldenmatch. This requires installing the Ink peer dependencies.

```bash
npx goldenmatch-js tui
```

--------------------------------

### CLI Command: Run Demo

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/typescript/goldenmatch/README.md

Executes a quick demonstration using synthetic data.

```bash
goldenmatch-js demo
```

--------------------------------

### AutoConfig and Telemetry Examples

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenmatch/docs/sql-duckdb.md

Demonstrates DuckDB UDFs for running autoconfiguration and retrieving controller telemetry. Includes examples for `goldenmatch_autoconfig`, `goldenmatch_autoconfig_telemetry`, and `goldenmatch_dedupe_full` with detailed configuration.

```sql
-- Run AutoConfigController on a table; get committed config JSON.
SELECT goldenmatch_autoconfig('customers');

-- Same call, but returns the controller telemetry blob (stop_reason,
-- health, decisions, indicator priors, committed NE).
SELECT goldenmatch_autoconfig_telemetry('customers');

-- Run dedupe with a *full* GoldenMatchConfig JSON. Unlike the slim
-- `goldenmatch_dedupe_table` kwargs, this accepts `negative_evidence`
-- (Path Y) and every other Pydantic field.
SELECT goldenmatch_dedupe_full('customers', '{
    "matchkeys": [
        {"name": "exact_email", "type": "exact",
         "fields": [{"field": "email", "transforms": ["lowercase"]}],
         "negative_evidence": [
             {"field": "phone", "scorer": "exact",
              "transforms": ["digits_only"], "threshold": 0.5, "penalty": 0.5}
         ]}
    ]
}');

-- Job pipeline: gm_run captures controller telemetry into in-memory state.
SELECT gm_configure('cust_job', '{"exact": ["email"]}');
SELECT gm_run('cust_job', 'customers');
SELECT gm_telemetry('cust_job');   -- last run's telemetry JSON
```

--------------------------------

### Docker Installation and Usage

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/rust/extensions/README.md

Run GoldenMatch extensions using Docker for a zero-configuration setup. Connect to the PostgreSQL instance and execute queries.

```bash
docker run -p 5432:5432 -e POSTGRES_PASSWORD=postgres ghcr.io/benseverndev-oss/goldenmatch-extensions:latest
# Extension is pre-installed. Connect and use:
psql -h localhost -U postgres -c "SELECT goldenmatch.goldenmatch_score('John', 'Jon', 'jaro_winkler');"
```

--------------------------------

### goldenmatch_explain Example

Source: https://github.com/benzsevern/goldenmatch/blob/main/packages/python/goldenmatch/docs/sql-duckdb.md

Use `goldenmatch_explain` to get a natural language explanation of a match decision between two JSON records based on a fuzzy matching configuration.

```sql
SELECT goldenmatch_explain(
    '{"name": "John Smith"}',
    '{"name": "Jon Smyth"}',
    '{"fuzzy": {"name": 1.0}}'
);
```