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Found 12 Skills
Build React TypeScript web applications using Docyrus as a backend. Use when creating or modifying apps that authenticate with Docyrus OAuth2, fetch/mutate data via the @docyrus/api-client library, use auto-generated collections for CRUD operations, or build queries with filters, aggregations, formulas, pivots, and child queries against Docyrus data sources. Triggers on tasks involving @docyrus/api-client, @docyrus/signin, Docyrus collections, data source queries, or Docyrus-backed React app development.
Write and debug TypeQL queries for TypeDB 3.8+. Use when working with TypeDB schemas, data queries, insertions, deletions, or functions. Covers schema definition, CRUD operations, pattern matching, aggregations, and common pitfalls.
Implements Syncfusion DataManager for local/remote binding, CRUD, querying, caching, and middleware. Supports JsonAdaptor, ODataAdaptor, ODataV4Adaptor, UrlAdaptor, WebApiAdaptor, WebMethodAdaptor, RemoteSaveAdaptor, GraphQLAdaptor, CustomDataAdaptor, and CustomAdaptor. Covers Query class, filtering, sorting, paging, grouping, persistence, offline mode, caching, and error handling.
Explore and query any dataset annotated with a Frictionless Data Package descriptor (datapackage.json). Use this skill whenever a user wants to discover what tables or resources a dataset contains, look up column names and descriptions, surface usage warnings embedded in metadata, or understand how to load data from Parquet files, DuckDB or SQLite databases, or CSV files described by a datapackage.json. Also use when the user has a datapackage.json and wants to know what's in it, how to query it efficiently, or how to connect its metadata to actual data files. Pairs well with dataset-specific skills (like `pudl`) that layer domain knowledge on top.
Enables Claude to create, manage, and query databases in Airtable via Playwright MCP
Gate Exchange affiliate program data query and management skill. Use this skill when users ask about their affiliate/partner commission, trading volume, net fees, customer count, trading users, or want to apply for the affiliate program. Supports queries for up to 180 days (API limited to 30 days per request, agent should split longer queries). IMPORTANT: user_id parameter in APIs refers to 'trader' not 'commission receiver' - avoid using unless explicitly specified. Aggregated data from API lists should be calculated using custom scripts, not simple summation. CRITICAL TIME CONSTRAINT: All query times are calculated based on user's system current date in UTC+8 timezone. For relative time descriptions (e.g., 'last 7 days', 'last 30 days', 'this week', 'last month'), calculate start date by subtracting days from current date, then convert both start and end dates to UTC+8 00:00:00 and 23:59:59 respectively, then convert to Unix timestamps. NEVER use future timestamps as query conditions. When timestamps are needed, obtain them via system functions, never generate manually. The 'to' parameter must always be less than or equal to the current Unix timestamp. Trigger phrases include 'my affiliate data', 'commission this week', 'partner earnings', 'team performance', 'customer trading volume', 'rebate income', 'apply for affiliate', 'can I apply', 'am I eligible', 'my application status', 'recent application', 'partner application status'.
Write and run AQL (Analytic Query Language) queries to answer data questions. Use this whenever the user asks for data, wants to query a dataset, needs to filter/aggregate/join data, or asks about metrics and dimensions in Holistics.
Quick reference for the Caffeine Data Intelligence agent to query an OQL-exposing canister (schema() + execute()) through the `icp` CLI against the project's `backend` canister: read the schema, form JSON queries (filter / order / paginate / aggregate / dotted-path edges), and parse the Candid result rows.
Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.
Guides exploration of $autocapture events captured by posthog-js to understand user interactions, find CSS selectors (especially data-attr attributes), evaluate selector uniqueness, query matching clicks ad-hoc, and create actions. Use when the user asks about autocapture data, wants to find what users are clicking, needs to build actions from click events, asks about elements_chain, wants to build a trend or funnel filtered by clicks or other autocapture interactions, asks which properties autocapture sends, or asks how to filter $autocapture events. Only applies to projects using posthog-js autocapture.
Queries local Granola meeting cache for meeting history, context, and attendee information. Use when preparing for meetings, researching past interactions with a person or company, finding past discussions on a topic, tracking engagement, or when user mentions Granola, meeting notes, meeting history, or attendees.
HogQL queries for PostHog analytics