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概要と使いどころ
Specialist for the entire job application process. Analyzes job postings, optimizes profiles (LinkedIn/CV), and generates tailored cover letters. Generates ASCII CVs from a SQLite database and folder structure. cv_generator.py is ported standalone -- no BACH runtime required.
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Especialista para todo el proceso de solicitud de empleo. Analiza ofertas de trabajo, optimiza perfiles (LinkedIn/CV) y genera cartas de presentación personalizadas. Genera CVs en ASCII a partir de una base de datos SQLite y una estructura de carpetas. cv_generator.py está adaptado de forma independiente -- no requiere la ejecución de BACH.
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Spezialist fuer den gesamten Bewerbungsprozess. Analysiert Stellenanzeigen, optimiert Profile (LinkedIn/CV) und generiert massgeschneiderte Anschreiben. Generiert ASCII-Lebenslaeufe aus einer SQLite-Datenbank und Ordnerstruktur. cv_generator.py ist standalone portiert -- keine BACH-Runtime noetig.
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Creates a personalised daily newspaper from RSS feeds and web sources. Ported from the BACH news system (news.py + newspaper_generator.py). Own SQLite store (no Origin-DB). feedparser optional — XML fallback via stdlib. PDF export via Edge Headless (msedge.exe).
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Local, private capture of medical data: diagnoses, symptom histories and examination plans. No BACH origin — custom design with its own SQLite store. Strictly local, no cloud transfer.
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Calendar skill with user-adaptive backend selection (Flag 3). Default: local SQLite store. Optional: Google Calendar MCP, Routinika or UpToday as backend — controlled via assist/prefs.json. Without preference the LLM asks the user interactively.
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Create an Estuary derivation that maintains a sliding time window of events (e.g. "transfers in the last 24h", "failed logins in the last 5 minutes") using internal SQLite state and readDelay for time-based expiration. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this. Use when user says "windowing derivation", "derivation for last-24h events", "rolling-window derivation", "sliding-window transformation", "fraud-detection derivation", "rate-limit derivation", or "time-window derivation".
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Create an Estuary derivation with custom SQLite state (internal tables) to make per-document decisions based on accumulated history — account balances, inventory levels, approval workflows, deduplication. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this. Use when user says "stateful derivation", "derivation to track balance", "transformation to approve based on state", "derive an approval workflow", "deduplication derivation", or "build a stateful derivation".
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Write Estuary derivations in Python — async-generator transforms, Pydantic-typed source/output, optional persistent state, and dependency installation via uv. Use for ML/embeddings, async API calls, or any transform where SQL and TypeScript are awkward. Derivations add complexity and cost (and Python derivations require a private/BYOC data plane) — confirm the user wants a Python derivation before reaching for this. Use when user says "python derivation", "write a derivation in python", "embed with a python derivation", "ML derivation", "call an API from a derivation", or anything mentioning model2vec / huggingface / pydantic in a derivation context.
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Create an Estuary derivation that joins two or more collections on a shared key, merging their fields into a single enriched collection. Use for data enrichment, denormalisation, building wide tables for BI, and real-time CDC joins. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this (a destination-side SQL join or BI tool view is often simpler). Use when user says "join-collections derivation", "derivation to join two collections", "transformation to enrich with customer data", "derive a wide table", "lookup-join derivation", or "build a join derivation".
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Foundation for writing Estuary derivations — what they are, language choice (SQL/TypeScript/Python), project layout, flowctl workflow, stateless vs stateful shuffling, and universal gotchas. Read this before any other derivation-* skill. Use when user says "write a derivation", "how do derivations work", "create a derivation", "derivation setup", or before starting any transformation work.
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Develops full-stack Dart backends using the Serverpod framework with PostgreSQL, Redis, and Docker. Use when building type-safe API endpoints, defining YAML data models, configuring Serverpod auth, writing server-side tests, running database migrations, deploying to Docker/AWS/GCP, or using Serverpod Mini for database-less BFF proxy endpoints.
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Supabase Flutter integration for PostgreSQL, Auth, Realtime subscriptions, Storage, Edge Functions, and Row Level Security. Use when building backend features with supabase_flutter or configuring database policies.
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Builds React Native and Expo apps in TypeScript — navigation with React Navigation or Expo Router, lists, forms, styling, gestures and animations with Reanimated, safe areas, accessibility and localization; networking with TanStack Query, response validation, persistence with MMKV, AsyncStorage, SQLite and secure storage; permissions, push notifications, deep links, background tasks, native modules and config plugins; performance with Hermes and the React profiler; and release with EAS Build, EAS Submit and EAS Update or bare Gradle and Xcode builds. Use when writing or changing React Native code, adding a native capability, configuring Expo, preparing a store build or an over-the-air update, or when the user asks how to do something in React Native, even if they do not name the library.
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Use when a project follows a structured operating model with: two work lanes (Domain, System), unresolved work tracked as Epic, bounded execution tracked as Ticket, role-based behavior (architect, runner), helper-backed SQLite workflow tables, inbox and outbox files as task and result bodies.
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Connect to Azure Database for PostgreSQL Flexible Server from Node.js/TypeScript using the pg (node-postgres) package.
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Azure Cosmos DB SDK for Rust (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data.
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Azure Tables SDK for Python (Storage and Cosmos DB). Use for NoSQL key-value storage, entity CRUD, and batch operations.
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Build table storage applications with Azure Tables SDK for Java. Use when working with Azure Table Storage or Cosmos DB Table API for NoSQL key-value data, schemaless storage, or structured data at...
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Azure Cosmos DB SDK for Python (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data.
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Azure Cosmos DB SDK for Java. NoSQL database operations with global distribution, multi-model support, and reactive patterns.
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Build Azure Cosmos DB NoSQL services with Python/FastAPI following production-grade patterns. Use when implementing database client setup with dual auth (DefaultAzureCredential + emulator), service...
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Daily attendance register: check-in and check-out, hours worked, work mode, late minutes, leave and regularisation flags, as CSV, SQL, JSON Schema or Notion on request. Use for payroll input.
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Asset and IT register: serial, model, condition, assignee, location, purchase value, warranty expiry and return date, as CSV, SQL, JSON Schema or Notion on request. Use for asset audits.
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