neon
Neon integration. Manage Organizations, Users, Goals, Filters. Use when the user wants to interact with Neon data.
Skills
Find an Agent Skill for your task. Read the guide and copy the install command.
Updated 10-20 00:13
Data & analytics
16,571 results
porter
Porter integration. Manage data, records, and automate workflows. Use when the user wants to interact with Porter data.
qdrant
Qdrant integration. Manage Collections, Snapshots. Use when the user wants to interact with Qdrant data.
splunk
Splunk integration. Manage data, records, and automate workflows. Use when the user wants to interact with Splunk data.
linear-import
Import issues from CSV or JSON files. Use when bulk-creating issues from external data.
review-hog-perspective-logic-correctness
The Logic & Correctness review perspective for PostHog Review. Verifies that changed code does what it is supposed to do: business logic, edge cases, data…
zomato-ai-data-engineering-pipeline
End-to-end batch data pipeline with Snowflake, dbt, Airflow, and OpenAI for food delivery analytics
field-extraction-and-cim-mapping
Author, explain, diagnose, and validate Splunk search-time field extractions and mappings to Common Information Model (CIM) datasets from representative…
spree-data-model
Use when the user is asking how Spree's domain models relate — Orders, LineItems, Variants, Products, Stores, Channels, Markets, Payments, Shipments,…
analytics-tracking
When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google…
dragon-tiger-list-analyzer
Analyze Dragon-Tiger List data (institutional seats, brokerage branches, buy/sell movements, individual stock listing statistics) to identify capital preferences and abnormal trading risks. Use when users ask about the Dragon-Tiger List, institutional seat movements, hot money brokerage branches, reasons for listing, or need Dragon-Tiger List review.
crypto-backtest
Backtest crypto trading strategies from natural language ideas. Use when: user describes trading ideas, wants to validate strategies, mentions "backtest",…
drone-site-survey
Process drone survey data for construction sites. Generate orthomosaics, DEMs, point clouds, calculate volumes, track progress, and integrate with BIM models…
funnel-audit
Find funnel drop-offs from stage numbers you give or connected data, benchmarked, ranked by revenue. "where are we losing people"
cloud-gcp
Use this skill when architecting on Google Cloud Platform, selecting GCP services, or implementing data and compute solutions. Triggers on Cloud Run, BigQuery,…
process-street
Process Street integration. Manage Organizations, Integrations. Use when the user wants to interact with Process Street data.
explore-lakehouse
Inspect the RevOS BigQuery lakehouse: list datasets and tables, introspect table schemas and column types, preview sample rows, assess data layers…
frappe-errors-database
Use when handling database errors in Frappe/ERPNext. Covers DuplicateEntryError, LinkValidationError, MandatoryError, TimestampMismatchError,…
docusign
DocuSign integration. Manage data, records, and automate workflows. Use when the user wants to interact with DocuSign data.
formance
Formance integration. Manage data, records, and automate workflows. Use when the user wants to interact with Formance data.
integrated-finance
Integrated Finance integration. Manage data, records, and automate workflows. Use when the user wants to interact with Integrated Finance data.
rafay-systems
Rafay Systems integration. Manage data, records, and automate workflows. Use when the user wants to interact with Rafay Systems data.
data-visualization
Comprehensive data visualization skill covering visual execution and technical implementation. Includes perceptual foundations, chart selection, layout…
audit-ml-pipeline
Read-only audit of one persisted skore report: `audit/NN_<stem>.py` (jupytext percent), 1:1 with `experiments/` and `journal/`. Do not execute it. Run `materialize.py` once. Never call `skore.evaluate` or `project.put`. TRIGGER when a completed run needs an audit, the user asks to audit, show, or re-audit an experiment, a re-run overwrote the same `put()` key, or they want a narrative of a past experiment without `journal/ideas/` files. STOP when `status.setup.pending` is non-empty (load `setup-ml-project`), or when there is no approved design, no report, or no agent feature: explain and send the user to setup, `evaluate-ml-pipeline`, or `model-ml-pipeline`. Also stop for raw-data exploration or sourcing a future experiment. HOW TO USE: confirm journal, experiment, smoke, and report; place the file from `templates/audit.py`; copy `templates/materialize.py` to scratch; execute once; derive G-AUDIT-FINDING; then the continue-or-close gate. Resolve skore symbols with `api get`.