Results for “query skill”

Use when designing, reviewing, modifying, migrating, optimizing, securing, operating, troubleshooting, or decommissioning data architectures across data model exploration, SQL, ISO SQL conformance, NoSQL, vector, graph, document, time-series, NewSQL, search, in-memory, SQLite, CDC/Debezium, DBMS storage/query/recovery internals, database incident prevention, hardware acceleration, cache, big-data, lakehouse, and warehouse systems.

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Author and submit a Narrative workflow from a natural-language intent. Picks the closest example from `assets/examples/`, adapts it to the user's case, walks the YAML against the spec, resolves the data plane, and submits via `narrative_workflows_create` only after the user has approved the rendered spec. Use when: "create a workflow that does X", "schedule a daily refresh of dataset Y", "wrap this NQL as a workflow", "build a pipeline that creates view A then refreshes view B", "submit this workflow YAML", "productionize this query as a recurring job". (narrative-common)

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Produce a coverage & quality profile of a Narrative dataset (or access rule): row count, per-column null/fill rate, cardinality, ranges, top-values, inferred column shape, and quality flags. Reads bundled stats + sample first, recovers missing/stale stats by configuring and recalculating them, and escalates to a cheap `/write-nql` query only for a measure no stat can provide. Descriptive, not prescriptive. Use when: "profile dataset N", "what does dataset N look like", "coverage and quality of <dataset>", "what id types does N emit", "null rates / cardinality for <dataset>", "is this dataset's stats fresh". (narrative-common)

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Register a Snowflake table or view as a Narrative dataset from SQL, with no Configuration screen and no browser. Not for installing or configuring the native app, and not for querying a dataset that already exists. Use when: "register this table as a dataset", "register a Snowflake dataset from SQL", "onboard my_table to Narrative", "script dataset registration", "add this view to my data plane". (narrative-common)

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Retired. Project orientation moved to the remember skill (`/remember --project <name>` with no query). Use remember instead.

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Given the product offering and existing page inventory, create new core landing and resource pages (homepage refresh, features, solutions, pricing, comparison, resource hubs, about) that capture core product intent using the query-fanout pattern. Use this skill whenever the user asks to "spawn pages", "generate landing pages", "create marketing pages", "build a pricing page", "add a solutions page", "build out the site", "fill in missing pages", or wants new top-level marketing/product pages. Output is one new page per route in the project's native file format (component or markdown), matching the existing page style and framework idiom.

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Automate Attio CRM operations -- search records, query contacts and companies with advanced filters, manage notes, list attributes, and navigate your relationship data -- using natural language throug

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Validates whether an API request is correct based on provided inputs (method, URL, headers, body, auth, query params).

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Canonical patterns for writing custom MSBuild targets. Only activate in MSBuild/.NET build context. USE FOR: diagnosing and fixing custom target authoring anti-patterns, reviewing MSBuild target definitions for correctness, diagnosing broken SDK target chains across files (e.g., Directory.Build.targets silently redefining SDK targets), fixing targets that replace CompileDependsOn instead of extending it with $(CompileDependsOn), fixing query targets that return stale results due to Outputs vs Returns misuse, fixing missing Inputs/Outputs causing unnecessary rebuilds, fixing missing FileWrites registration. Covers DependsOnTargets vs BeforeTargets vs AfterTargets, the Build→CoreBuild three-level pattern, hooking into the build pipeline, the $(XxxDependsOn) chain-extension pattern. DO NOT USE FOR: incremental build tuning (use incremental-build), parallelization (use build-parallelism), general anti-patterns (use msbuild-antipatterns), non-MSBuild build systems.

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Expert guidance for LlamaIndex development including RAG applications, vector stores, document processing, query engines, and building production AI applications.

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SQL query optimization, schema design, indexing strategies, and relational database mastery for production data systems

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Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.

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Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

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Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures.

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Snowflake, BigQuery, Redshift, dimensional modeling, and modern data warehouse architecture

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Guidelines for developing with Kysely, a type-safe TypeScript SQL query builder with autocompletion support

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PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management.

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Transform slow database queries into lightning-fast operations through systematic optimization, proper indexing, and query plan analysis.

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Implements declarative Flutter routing using GoRouter v17 with URL-based navigation, deep linking, and authentication guards. Activates when configuring GoRoute path patterns, setting up StatefulShellRoute for persistent bottom navigation state, implementing ShellRoute for shared nested layouts, adding redirect guards with loop prevention (idempotent redirects), configuring deep links for iOS (FlutterDeepLinkingEnabled) or Android (intent-filters), debugging redirect loops or navigation stack issues, handling 404 error routes with errorBuilder, using named routes with path/query/extra parameters, or migrating from imperative Navigator.push to declarative routing. Ideal for Flutter web apps requiring URL bar synchronization, mobile apps with universal links or app links, or multi-level navigation hierarchies.

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Reads an OpenAPI 3.0 specification and manually implements a type-safe Dart API layer using Dio for HTTP, Freezed or Equatable for models, and json_serializable for serialisation. Use when given an OpenAPI/Swagger file (JSON or YAML) and asked to implement the API in Flutter/Dart, create Dart models from an API schema, build a Dio API client, implement endpoints from a spec, convert openapi to dart, or set up a data/network layer from an API contract. Handles $ref resolution, oneOf union types, enums, query params, request bodies, and DioException error mapping.

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Implements type-safe Flutter routing using AutoRoute v11 with code generation and @RoutePage annotations. Activates when setting up AutoRoute navigation, configuring AutoRouterConfig or RootStackRouter, generating route files with build_runner, using @RoutePage, @PathParam, or @QueryParam annotations, implementing AutoTabsRouter for bottom navigation tabs, adding navigation guards with AutoRouteGuard, setting up nested or child routes, handling type-safe route parameters, or migrating from string-based Navigator routing to compile-time-verified routes. Ideal for large apps requiring refactoring confidence and zero string-based routing errors.

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ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

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Set up a monday.com account for an OpenClaw agent and work with monday.com boards, items, and updates via the GraphQL API or MCP server. Use when: creating a monday.com workspace for a PA, connecting the PA to monday.com, querying boards and items, creating or updating items, troubleshooting monday.com API access, self-registering an agent on monday.com via HATCHA agent verification, or integrating with monday.com workflows. Covers GraphQL cookbook, column types, MCP configuration, and HATCHA self-registration. Works with any LLM model.

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Use when working with Cube Dev — cube.dev semantic layer management — monitor deployments, data models, pre-aggregations, query performance, and API health. Use when inspecting cube schemas, debugging slow queries, reviewing pre-aggregation builds, or auditing API usage.

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