firebase-data-connect
Builds and deploys Firebase SQL Connect (aka Firebase Data Connect) backends with PostgreSQL securely. Use when designing schemas with tables and relations, writing authorized queries and mutations, configuring real-time data updates, or generating type-safe SDKs. Use when you need a relational database with Firebase, or when the user mentions SQL Connect or Data Connect.
DeepseekModel
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v1.0.0
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name firebase-data-connect description Builds and deploys Firebase SQL Connect (aka Firebase Data Connect) backends with PostgreSQL securely. Use when designing schemas with tables and relations, writing authorized queries and mutations, configuring real-time data updates, or generating type-safe SDKs. Use when you need a relational database with Firebase, or when the user mentions SQL Connect or Data Connect. metadata {"category":"Databases"} Firebase SQL Connect Firebase SQL Connect is a relational database service using Cloud SQL for PostgreSQL with GraphQL schema, auto-generated queries/mutations, and type-safe SDKs. [!NOTE] Product Rename : Firebase Data Connect was renamed to Firebase SQL Connect . All instructions, references, and examples in this skill repository referring to "Data Connect" or "Firebase Data Connect" apply to "SQL Connect" and "Firebase SQL Connect" as well. Project Structure dataconnect/ ├── dataconnect.yaml # Service configuration ├── seed_data.gql # LOCAL ONLY — prototype/test data ├── schema/ │ └── schema.gql # Data model (types with @table) └── connector/ ├── connector.yaml # Connector config + SDK generation ├── queries.gql # Queries └── mutations.gql # Mutations Key Tools for Validation Rely on these two mechanisms to ensure project correctness: Review GraphQL Schema : Both user-defined and generated extensions (in .dataconnect/schema/main/ ). Validate Operations : Run npx -y firebase-tools@latest dataconnect:compile against the schema. Operation Strategies: GraphQL vs. Native SQL Always default to Native GraphQL . Native SQL lacks type safety and bypasses schema-enforced structures. Only use Native SQL when the user explicitly requests it or when the task requires advanced database features. Strategy When to use Implementation Native GraphQL (Default) Almost all use cases. Standard CRUD, basic filtering/sorting, simple relational joins. Requires full type safety. Auto-generated fields ( movie_insert , movies ). Strong typing and schema enforcement. Native SQL (Advanced) PostgreSQL extensions (e.g., PostGIS), window functions ( RANK() ), complex aggregations, or highly tuned sub-queries. Raw SQL string literals via _select , _execute , etc. Requires strict positional parameters ( $1 ). No type safety. Development Workflow Follow this strict workflow to build your application. You must read the linked reference files for each step to understand the syntax and available features. 1. Define Data Model ( schema/schema.gql ) Define your GraphQL types, tables, and relationships (which map to a Postgres schema). Read reference/schema.md for: @table , @col , @default Relationships ( @ref , one-to-many, many-to-many) Data types (UUID, Vector, JSON, etc.) 2. Define Authorized Operations ( connector/queries.gql , connector/mutations.gql ) Write the queries and mutations your client will use, including authorization logic. SQL Connect is secure by default. Read reference/operations.md for: Queries : Filtering ( where ), Ordering ( orderBy ), Pagination ( limit / offset ). Mutations : Create ( _insert ), Update ( _update ), Delete ( _delete ). Upserts : Use _upsert to "insert or update" records (CRITICAL for user profiles). Transactions : Use @transaction for multi-step atomic operations. Use _expr: "response.<prevStep>" to pass data between steps. Read reference/security.md for authorization: @auth(level: ...) for PUBLIC, USER, or NO_ACCESS. @check and @redact for row-level security and validation. Read reference/realtime.md for real-time subscriptions: @refresh directive for time-based polling and event-driven updates. CEL conditions to scope refresh triggers precisely. Read reference/native_sql.md for Native SQL operations: Embedding raw SQL with _select , _selectFirst , _execute Strict rules for positional parameters ( $1 , $2 ), quoting, and CTEs Advanced PostgreSQL features (PostGIS, Window Functions) 3. Use type-safe SDK in your apps Generate type-safe code for your client platform. Configure SDK generation in connector.yaml : connectorId: my-connector generate: javascriptSdk: outputDir: "../web-app/src/lib/dataconnect" package: "@movie-app/dataconnect" kotlinSdk: outputDir: "../android-app/app/src/main/kotlin/com/example/dataconnect" package: "com.example.dataconnect" swiftSdk: outputDir: "../ios-app/DataConnect" Generate SDKs: npx -y firebase-tools@latest dataconnect:sdk:generate For platform-specific instructions on how to use the generated SDKs, read: Web (TypeScript) : reference/sdk_web.md Android (Kotlin) : reference/sdk_android.md iOS (Swift) : reference/sdk_ios.md Admin (Node.js) : reference/sdk_admin_node.md Flutter (Dart) : reference/sdk_flutter.md Feature Capability Map If you need to implement a specific feature, consult the mapped reference file: Feature Reference File Key Concepts Data Modeling reference/schema.md @table , @unique , @index , Relations Vector Search reference/search.md Vector , @col(dataType: "vector") , embeddings Full-Text Search reference/search.md @searchable , movies_search Upserting Data reference/operations.md _upsert mutations Complex Filters reference/operations.md _or , _and , _not , eq , contains Transactions reference/operations.md @transaction , response binding Environment Config reference/config.md dataconnect.yaml , connector.yaml Realtime Subscriptions reference/realtime.md @refresh , subscribe() , auto-refresh Cloud Functions Integration reference/cloud_functions.md onMutationExecuted , triggering events Data Seeding & Migrations reference/data_seeding.md seed_data.gql , _insertMany , Admin SDK bulk Starter Templates templates.md CRUD, user-owned resources, many-to-many, SDK init Deployment & CLI Read reference/config.md for deep dive on configuration. Follow these patterns based on your current task: How to initialize SQL Connect in a Firebase project Understand the app idea. Ask clarification questions if unclear. Run npx -y firebase-tools@latest init dataconnect . Validate that the app template and generated SDK are setup. How to build apps using SQL Connect locally Start the emulator: npx -y firebase-tools@latest emulators:start --only dataconnect . Write schema and operations. Seed local test data into seed_data.gql . Read reference/data_seeding.md . Run npx -y firebase-tools@latest dataconnect:compile or npx -y firebase-tools@latest dataconnect:sdk:generate to validate them. Use the operations in your app and build it. How to deploy SQL Connect to Cloud SQL Run npx -y firebase-tools@latest deploy --only dataconnect . Examples For complete, working code examples of schemas and operations, see examples.md . For ready-to-use starter templates (CRUD, user-owned resources, many-to-many, YAML configs, SDK init), see templates.md .
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|---|---|
| format | フォーマット識別子(skill/v1) |
| skill_id | スキル固有 ID |
| name | スキル名 |
| version | バージョン |
| description | 説明 |
| category | カテゴリ(配列) |
| trigger_words | トリガーワード |
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| model_config | モデル設定:provider / model / temperature / max_tokens / top_p |
| examples | サンプル |
| install_guide | 各プラットフォームの導入説明(Coze / Dify / Claude / カスタム) |