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docs: make skill docs changes (#107)
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DEVELOPER.md

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# DEVELOPER.md
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This document provides instructions for setting up your development environment
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and contributing to the Knowledge Catalog (formerly known as Dataplex) Gemini CLI Extension project.
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and contributing to the Knowledge Catalog (formerly known as Dataplex) Agent skills project.
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## Prerequisites
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### Running from Local Source
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The core logic for this extension is handled by a pre-built `toolbox` binary. The development process involves installing the extension locally into the Gemini CLI to test changes.
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1. **Clone the Repository:**
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```bash
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git clone https://github.com/gemini-cli-extensions/knowledge-catalog.git
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cd knowledge-catalog
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```
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2. **Download the Toolbox Binary:** The required version of the `toolbox` binary
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is specified in `toolbox_version.txt`. Download it for your platform.
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```bash
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# Read the required version
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VERSION=$(cat toolbox_version.txt)
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# Example for macOS/amd64
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curl -L -o toolbox https://storage.googleapis.com/mcp-toolbox-for-databases/geminicli/v$VERSION/darwin/amd64/toolbox
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chmod +x toolbox
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```
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Adjust the URL for your operating system (`linux/amd64`, `darwin/arm64`, `windows/amd64`).
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3. **Link the Extension Locally:** Use the Gemini CLI to install the
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2. **Install the Extension Locally:** Use the Gemini CLI to install the
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extension from your local directory.
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```bash
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gemini extensions link .
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gemini extensions install .
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```
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The CLI will prompt you to confirm the linking. Accept it to proceed.
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The CLI will prompt you to confirm the installation. Accept it to proceed.
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4. **Testing Changes:** After linking, start the Gemini CLI (`gemini`).
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You can now interact with the `knowledge-catalog` tools to manually test your changes
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against your connected database.
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3. **Testing Changes:** After installation, start the Gemini CLI (`gemini`).
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You can now interact with the `knowledge-catalog` skills to manually test your changes.
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## Testing
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for every pull request. This workflow primarily verifies that the extension can
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be successfully installed by the Gemini CLI.
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Currently, there are no automated unit or integration test suites
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within this repository. All functional testing must be performed manually. All tools
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are currently tested in the [MCP Toolbox GitHub](https://github.com/googleapis/mcp-toolbox).
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All skills are currently tested in the [MCP Toolbox GitHub](https://github.com/googleapis/mcp-toolbox).
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The skills themselves are validated using the `skills-validate.yml` workflow.
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### Other GitHub Checks
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* **Dependency Updates:** [Renovate](https://github.com/apps/forking-renovate)
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is configured to automatically create pull requests for dependency updates.
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## Maintainer Information
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### Team

KNOWLEDGE_CATALOG.md

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To install this extension, the Gemini CLI version must be v0.6.0 or above. The version can be found by running: `gemini --version`.
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## Knowledge Catalog(formerly known as Dataplex) MCP Server (Data Plane: Connecting and Querying)
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## Knowledge Catalog (formerly known as Dataplex) Agent Skills (Data Plane: Connecting and Querying)
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This section covers connecting to a Knowledge Catalog instance.
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1. **Verify Environment Variables**: The extension requires the following environment variables to be set before the Gemini CLI is started:
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1. **Verify Environment Variables**: The extension requires the following environment variables to be set before the agent is started:
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* `DATAPLEX_PROJECT`: The GCP project ID.
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---
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# Usage Guidelines
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## Reusing Project Values
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Users may have set project environment variables:
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* `DATAPLEX_PROJECT`: The GCP project ID.
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Instead of prompting the user for these values for specific skill calls, prompt the user to verify the reuse of a specific setting value.
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Make sure to not use the environment variable name like `DATAPLEX_PROJECT`, `${DATAPLEX_PROJECT}`, or `$DATAPLEX_PROJECT`.
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The value can be verified by the user using the `gemini extensions config knowledge-catalog` command or by checking their local settings.
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---
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# Data Model
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## Entries
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Entries can be linked together using EntryLinks to represent relationships between data assets (e.g. foreign keys).
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# Tool instructions
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# Skill instructions
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## Tool: search_entries
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## Skill: search_entries
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## General
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1. Explain that no search result was found
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2. Suggest to provide a more specific search query.
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## Tool: lookup_entry
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## Skill: lookup_entry
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### Request
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1. Always try to limit the size of the response by specifying `aspect_types` parameter. Make sure to include to select view=CUSTOM when using aspect_types parameter. If you do not know the name of the aspect type, use the `search_aspect_types` tool.
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2. If you do not know the name of the entry, use `search_entries` tool
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1. Always try to limit the size of the response by specifying `aspect_types` parameter. Make sure to include to select view=CUSTOM when using aspect_types parameter. If you do not know the name of the aspect type, use the `search_aspect_types` skill.
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2. If you do not know the name of the entry, use `search_entries` skill
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### Response
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