A three-stage development method for Python projects built with pydantic-resolve, starting with agreed data models and ending with application interfaces. It uses an ER diagram, which shows database entities and their relationships, plus ORM models that represent database records in code.
Model data in RushDB's property-centric LMPG graph. Use when designing or evolving schemas, choosing labels and properties, defining relationships, importing nested JSON, structuring a new use case, or modeling agent memory with EPISODE, MEMORYFACT, domain records, scope fields, semantic properties, and fact…
Design a tailored RushDB schema for any use case through guided conversation. Use this skill when a user is starting a new project, unsure what labels to define, asking "what records should I create", or wants a scaffold for a known domain (e-commerce, healthcare, SaaS, CRM, agent memory, etc.). Interviews the user…
Build RushDB queries, searches, filters, and aggregations. Use whenever an agent needs to list or filter records, count or group data, traverse relationships, run semantic/vector search, construct a findRecords call, discover live labels and properties, or recall canonical EPISODE and MEMORYFACT records with mandatory…
Manage OpenViking collections (OV libraries) from the command line with ov-cp — list / create / get / update / usage / get the data-plane API key / delete, plus managing the users of an enterprise-tier library (list / register / update / delete) and configuring how a library is billed (AgentPlan AFP deduction vs…
Refresh investment activities and card/bank expenses into familyoffice.db, then review spending. Investment activities come from the DB transactions table (SnapTrade); debit-card and bank spending comes from the DB banktransactions table (SimpleFIN), auto-categorized. Sync-first so nothing is stale. USE WHEN user…
Configure or use the aiocache caching layer. Use when: adding cache reads/writes, configuring cache backends, working with TTLs, enabling/disabling caching, or understanding the NoOpCache fallback pattern.
Create or modify SQLAlchemy models, queries, and Alembic migrations. Use when: defining new database tables, writing queries, creating migrations, checking model conventions, or understanding the database layer.
Expert guidance for better-drizzle repository work. Use whenever the user is building, refactoring, reviewing, debugging, documenting, or migrating code that uses better-drizzle, Drizzle delegates, plugins, transactions, pagination, filters, raw SQL, or performance-sensitive repository helpers. Also use when the task…
SQL injection detection and exploitation using sqlmap, manual techniques, and custom payloads. Use this skill when user needs to test for SQL injection vulnerabilities, extract database information, or exploit SQLi in parameters, headers, or cookies.
SQLite-based persistent storage and reporting system for penetration testing results. Use this skill when user needs to store scan results, query vulnerabilities, generate reports, or manage pentest data across sessions.
Create Databricks AI/BI dashboards. Must use when creating, updating, or deploying Lakeview dashboards as Databricks Dashboard have a unique json structure. CRITICAL: You MUST test ALL SQL queries via CLI BEFORE deploying. Follow guidelines strictly.
Develop Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables) on Databricks. Use when building batch or streaming data pipelines with Python or SQL. Invoke BEFORE starting implementation.
Add captions to a talking-head video. ONE catalog (CATALOG.md) of 32 visual identities behind two engines: column-flow (captions composited INTO the scene — matte occlusion + mix-blend; cream/ink/editorial/keynote/documentary/loud/neon/glitch/chrome/velocity) and themed constitutions…
Audit and design entity data models into a field-by-field markdown report: a target-vs-current audit table per entity, a classification of every field (table column / config blob / runtime-computed / remove), a grouped migration change list, and design-decision justifications. Use this whenever the user reasons about…
Use Dory as the official AI-native SQL workspace for agents. Use when the user asks to inspect or analyze databases, explore unknown schemas, debug data issues, run read-only SQL through Dory MCP, manage Dory Agent Runs, create or update SQL workspace tabs, work with saved queries, preserve query results, or hand SQL…
Create a new splinter lint — a SQL view that checks for a database anti-pattern. Use this skill when the user asks to add a lint, create a new check, implement a linting rule, or extend splinter with a new detection.
Run SQL queries across databases (Postgres, MySQL, SQLite, etc.) via the squix CLI. Use for running named queries, exploring schema, or parameterized queries. Always use -f for non-interactive output.
Ground a database schema change in this application's real structure using Laravel Truss. Use when adding or altering tables, columns, indexes, or foreign keys, when a migration needs to match what is already there, or when you need to know what a migration actually changed. Structure only, never data.
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At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: