create-data-source — Создание коннекторов данных для Kibana Workplace AI

--- name: create-data-source description: Creates a new Data Source for Workplace AI. Use when asked to create (or add) a new "fetcher", Data Source, or connector. allowed-tools: WebFetch, WebSearch, Read, Grep, Glob, Write, Edit, Bash, Skill context: fork argument-hint: [3rd-party-data-source-name] --- # Create a Data Source for Workplace AI We're going to create a new Data Source connector for **$0**. The intent is to provide connectors that enable "federated search" of third-party systems through Kibana's Workplace AI. ## Reference Materials - **[reference/data-source-patterns.md](reference/data-source-patterns.md)** — Directory structure, file templates, and registration patterns - **Workflow YAML syntax** — When you need to write or understand workflow YAML files, invoke the `workflows-yaml-reference` skill (use the Skill tool with `skill: "workflows-yaml-reference"`) ## Step 1: Determine the Connector Strategy Check if $0 has a suitable connector already available. If not, determine whether an official hosted MCP server exists for $0. **Use an MCP server?** → Read [reference/mcp-connector-setup.md](reference/mcp-connector-setup.md) and follow its steps. **No MCP server available?** → Read [reference/custom-connector-setup.md](reference/custom-connector-setup.md) and follow its steps. Follow only the steps for the chosen path. Do not mix them. ## Step 2: Create the Data Source Create the data source in `x-pack/platform/plugins/shared/data_sources/server/sources/{source_name}/`. Follow the patterns in [reference/data-source-patterns.md](reference/data-source-patterns.md): 1. **`data_type.ts`** — DataSource definition with id, name, description, iconType, workflows directory, and: - **MCP path:** `stackConnectors` (array) with `type: '.mcp'`, MCP server URL, auth type, and `importedTools`. See the GitHub data source (`server/sources/github/data_type.ts`) for the pattern. - **Custom connector path:** `stackConnector` (singular) with `type: '.<connector-id>'` matching the connector spec ID. 2. **`index.ts`** — Re-export the data source 3. **`workflows/`** — YAML files (see Step 3) Register in `x-pack/platform/plugins/shared/data_sources/server/sources/index.ts`. Replace the placeholder icon with a proper brand icon. Search for existing SVG/PNG files in: - `x-pack/platform/plugins/shared/content_connectors/public/assets/icons/` - `x-pack/platform/plugins/shared/stack_connectors/public/connector_types/{connector}/` ## Step 3: Create Workflows Create YAML workflow files in the `workflows/` directory. For the full YAML schema, invoke the `workflows-yaml-reference` skill. Standard workflows: 1. **search.yaml** — Primary search. Focus on high-level metadata and matched text. 2. **get_{item}.yaml** — Retrieve specific items by ID. Include all metadata. 3. **list_{items}.yaml** — List available items/spaces/projects. Focus on high-level metadata. Remember: - Tag with `['agent-builder-tool']` to expose as AI tool - Use `<%= your-source-stack-connector-id %>` for connector-id, where your-source is the id of the newly created data source type - Use `${{ inputs.param_name }}` for input references ## Step 4: Create Tests Add tests following the existing examples: 1. **Connector spec tests** (custom connector path only) — See `google_drive/google_drive.test.ts` in `kbn-connector-specs` for the pattern. 2. **Workflow behavioral tests** — Add `workflows.test.ts` next to `data_type.ts`. See `google_drive/workflows.test.ts` or `slack/workflows.test.ts` for the pattern. You do not need to execute the tests — just create the files. ## Step 5: Write Documentation Create a connector doc page in `docs/reference/connectors-kibana/{name}-action-type.md`. ### Prerequisites This step requires documentation skills from https://github.com/elastic/elastic-docs-skills. Check availability by invoking `docs-check-style` (use the Skill tool). If it fails with "skill not found", stop and tell the user: > Documentation skills are not installed. Please install them: > > ```bash > curl -sSL https://raw.githubusercontent.com/elastic/elastic-docs-skills/main/install.sh | bash > ``` > > Then re-run this step. ### Write the doc page 1. Read 1–2 existing connector docs from `docs/reference/connectors-kibana/` as templates (for example, `zendesk-action-type.md`, `jira-cloud-action-type.md`). Follow the same structure. 2. Write the new doc page. Use `docs-syntax-help` if unsure about MyST Markdown syntax. 3. Run these skills on the new file and fix any issues: - `frontmatter-description` — generate the `description` frontmatter field - `page-opening-optimizer` — verify H1 and opening paragraph - `applies-to-tagging` — validate `applies_to` block - `docs-check-style` — check Elastic style guide compliance ### Update navigation and listings 1. Add an entry in `docs/reference/toc.yml` under the data and context sources connectors section. 2. Add a row in `docs/reference/connectors-kibana/_snippets/data-context-sources-connectors-list.md`. Once you are done developing the connector, data source, tests, and documentation, let the user review your work before next steps. ## Important Notes - **Stop if architectural gaps emerge** — This skill is for additions to the data source catalog, not for enhancing platform features - **Keep workflows focused on federated search** — Each workflow should help end users search or retrieve data from conversations - **Follow existing patterns** — Look at Notion, GitHub, and SharePoint data sources for reference - **DO NOT modify existing documentation** — There may be existing connectors with similar names. Do not modify their documentation files.