Plugins
2 plugins@openagentinternet
Open Agent Connect
Open Agent Connect from openagentinternet/open-agent-connect.
15 skills · plugin
@redpanda-data
Redpanda Data Skills
Agent Skills for Redpanda's five products — Streaming (Kafka-compatible engine), SQL (Oxla), Connect (incl. CDC connectors), Cloud (Serverless, BYOC, Dedicated), and the Agentic Data Plane — plus the rpk CLI. Grounded in Redpanda source, docs, and APIs.
32 skills · plugin
Results for “connect”
116 skillsMariadb Drop User
Explains MariaDB-specific behavior of DROP USER and RENAME USER, including multiple accounts per statement, IF EXISTS handling, active-connection warnings, and effects on privileges and definers. Use when writing or reviewing account-lifecycle SQL for MariaDB.
0
Sqlalchemy Python
Use for writing, reviewing, debugging, migrating, or testing SQLAlchemy 2.x Core or ORM code involving Engine, Connection, Session, mapped models, select statements, transactions, pooling, results, loading, or AsyncSession. Do not use for raw database SQL with no SQLAlchemy boundary, Alembic migration design, DuckDB relations, or database administration.
0 · bundle
Matlab Access Datafeed
Guide for accessing financial and economic data in MATLAB using the Datafeed Toolbox. Covers Bloomberg (market data via bloomberg/blp/bloombergHypermedia), FRED (Federal Reserve economic data via fredrs), and Haver Analytics (economic data via haver/haverdirect/haverview). Use when connecting to any of these data providers from MATLAB.
920 · bundle
Mariadb Information Functions
Reference for MariaDB information functions, covering session and server metadata such as LAST_INSERT_ID, ROW_COUNT, FOUND_ROWS, USER, and VERSION, with usage guidance for writing SQL that reads auto-increment IDs, row counts, and connection details.
0
Excel Python
Use for writing, reviewing, debugging, or testing Python code that inspects, edits, extracts, validates, preserves, or generates Excel .xlsx or .xlsm workbooks. Trigger on workbook contracts, formulas and cached values, Excel Tables, defined names, OOXML parts, types and precision, macros, charts, hidden sheets, external links, and semantic workbook verification. Do not use for CSV-only work, dataframe computation with no workbook boundary, Excel UI automation, recalculation, connection refresh, or macro execution.
0 · bundle
Enrichment Analyst
Your data-fill agent. Connect a contact-enrichment tool (contact-level) or a company-enrichment tool (company-level), or both for the full waterfall, to fill gaps on any list. Given a name plus a company, find email, phone, LinkedIn, and title. Given a domain, find headcount, funding, technographic profile, and hiring intent. Trigger on "enrich these contacts with emails", "find LinkedIn URLs for {list}", "get phone numbers for {contacts}", "who are the decision makers at {company}", "complete this prospect list", "enrich this CSV", "get the technographic stack for {company}", "fill in missing data on {list}", or any data-completion, list-enrichment, or contact-lookup question.
0
Pattern Analyst
Your won/lost/churn pattern analyst. Connect a CRM plus a product-analytics tool, then turn retrospective data into forward-looking action. Three modes. (1) WON, win pattern recognition that feeds your ICP and lookalike search. (2) LOST, loss pattern plus competitive intel that feeds a messaging refresh. (3) CHURN, churn theme extraction plus predictive scoring (which active accounts look like recent churners?). Trigger on "why are we winning?", "why are we losing?", "closed-lost autopsy", "churn patterns", "competitive intel rollup", "who do we lose to most?", "show me lookalike candidates to {winning customer}", "predictive churn", "which active accounts look like churners?", or any portfolio-level pattern recognition.
0
Matlab Use Duckdb
Use DuckDB from MATLAB via Database Toolbox (R2026a+) as a non-math operations engine on large tabular files (CSV/Parquet/JSON) and as a zero-config embedded database. Use when connecting to DuckDB, querying CSV, Parquet, and JSON files directly with SQL, reducing or profiling large data before MATLAB analysis, creating portable development databases, or installing DuckDB extensions. Triggers on: DuckDB, duckdb(), large CSV/Parquet/JSON, file too large for readtable, filter/aggregate at source, deduplicate, reduce before analysis, profile large file, persistent file import, analytical engine, SQL on CSV, SQL on Parquet, SQL on JSON, query CSV with SQL, query Parquet with SQL, run SQL on files, SQL queries on files, query files directly, SQL without database, in-process SQL.
920 · bundle