Data AI Skills
Transform raw data into actionable insights
Data skills turn unstructured information into structured analyses. Generate SQL queries, create data visualizations, build ETL pipelines, and produce executive summaries - all from natural language descriptions of what you need.
Top Data Skills
Popular Platform Data Collection Skill
Popular Platform Data Collection Skill is an agent workflow for authorized content research, content archiving, and first-party account backups. It guides users to manually export public, owned, or clearly authorized videos, cover images, page copy, tags, engagement data, and comments through DATATOOL. It validates the input files, uses local OpenAI Whisper to transcribe the complete video audio track, anonymizes comment data when requested, and produces a verifiable Chinese ZIP package containing Excel files, text, subtitles, segmented JSON, and a SHA-256 manifest. Users handle DATATOOL installation, login, verification, authorization, and content export in a normal browser. The Skill does not control DATATOOL, store cookies or passwords, bypass captchas, paywalls, private-content restrictions, or anti-bot controls. Videos are transcribed locally by default and are not uploaded to third-party transcription services.
agent-platform-model-registry
# Agent Platform Model Registry Management ## Overview This skill provides instructions for managing machine learning models in the Agent Platform Model Registry. It covers listing models, describing model details, uploading new models or versions, updating metadata, and deleting models. ## Safety & Confirmation Tiers (CRITICAL) Before executing any commands on behalf of the user, you MUST adhere to the following safety tiers based on the action requested: 1. **Tier R: Read-only (`list`, `describe`, `get`)*
agent-platform-eval-flywheel
# Agent Platform Eval Flywheel Skill Help users evaluate and iteratively improve GenAI models and agents using the Agent Platform GenAI Evaluation SDK (`google.genai` / `agentplatform`). ## When to use this skill - Evaluating GenAI agents or models with the Agent Platform GenAI Evaluation SDK (`client.evals.evaluate()`). - Creating evaluation datasets from session traces, pandas DataFrames, or synthetic generation. - Selecting, configuring, or writing custom evaluation metrics. - Analyzing rubric verdicts,
data-context-extractor
# Data Context Extractor A meta-skill that extracts company-specific data knowledge from analysts and generates tailored data analysis skills. ## How It Works This skill has two modes: 1. **Bootstrap Mode**: Create a new data analysis skill from scratch 2. **Iteration Mode**: Improve an existing skill by adding domain-specific reference files --- ## Bootstrap Mode Use when: User wants to create a new data context skill for their warehouse. ### Phase 1: Database Connection & Discovery **Step 1: Identify the
What data skills can do for you
Query Generation
Describe what you want in plain English and get optimized SQL, pandas code, or data transformation scripts. Skills understand complex joins, aggregations, and window functions.
Analysis & Visualization
Generate charts, dashboards, and statistical analyses from your data. Skills produce matplotlib, D3, or Chart.js code ready to embed in your applications.
Data Pipeline Tools
Build ETL workflows, data validation rules, and cleaning scripts. Skills handle common data problems like missing values, deduplication, and format standardization.
Data Skills at a Glance
| Skill | Type | Price | Downloads | Rating | Security |
|---|---|---|---|---|---|
| Popular Platform Data Collection Skill | Skill | $7 | 0 | — | Verified |
| agent-platform-model-registry | Agent | Free | 7.3k | — | Review |
| agent-platform-eval-flywheel | Agent | Free | 7.3k | — | Review |
| data-pipeline | Skill | Free | 1.1k | — | Review |
| data-context-extractor | Skill | Free | 3.0k | — | Review |
All Data Skills
Popular Platform Data Collection Skill
Popular Platform Data Collection Skill is an agent workflow for authorized content research, content archiving, and first-party account backups. It guides users to manually export public, owned, or clearly authorized videos, cover images, page copy, tags, engagement data, and comments through DATATOOL. It validates the input files, uses local OpenAI Whisper to transcribe the complete video audio track, anonymizes comment data when requested, and produces a verifiable Chinese ZIP package containing Excel files, text, subtitles, segmented JSON, and a SHA-256 manifest. Users handle DATATOOL installation, login, verification, authorization, and content export in a normal browser. The Skill does not control DATATOOL, store cookies or passwords, bypass captchas, paywalls, private-content restrictions, or anti-bot controls. Videos are transcribed locally by default and are not uploaded to third-party transcription services.
agent-platform-model-registry
# Agent Platform Model Registry Management ## Overview This skill provides instructions for managing machine learning models in the Agent Platform Model Registry. It covers listing models, describing model details, uploading new models or versions, updating metadata, and deleting models. ## Safety & Confirmation Tiers (CRITICAL) Before executing any commands on behalf of the user, you MUST adhere to the following safety tiers based on the action requested: 1. **Tier R: Read-only (`list`, `describe`, `get`)*
agent-platform-eval-flywheel
# Agent Platform Eval Flywheel Skill Help users evaluate and iteratively improve GenAI models and agents using the Agent Platform GenAI Evaluation SDK (`google.genai` / `agentplatform`). ## When to use this skill - Evaluating GenAI agents or models with the Agent Platform GenAI Evaluation SDK (`client.evals.evaluate()`). - Creating evaluation datasets from session traces, pandas DataFrames, or synthetic generation. - Selecting, configuring, or writing custom evaluation metrics. - Analyzing rubric verdicts,
data-pipeline
# Data Pipeline Build data pipelines and ETL workflows for data integration, transformation, and analytics automation. Based on n8n's data workflow templates. ## Overview This skill covers: - Data extraction from multiple sources - Transformation and cleaning - Loading to destinations - Scheduling and monitoring - Error handling and alerts --- ## ETL Patterns ### Basic ETL Flow ``` ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ EXTRACT │───▶│ TRANSFORM │───▶│ LOAD │ │ │ │ │ │ │ │ • APIs │ │ • Clean │ │ •
data-context-extractor
# Data Context Extractor A meta-skill that extracts company-specific data knowledge from analysts and generates tailored data analysis skills. ## How It Works This skill has two modes: 1. **Bootstrap Mode**: Create a new data analysis skill from scratch 2. **Iteration Mode**: Improve an existing skill by adding domain-specific reference files --- ## Bootstrap Mode Use when: User wants to create a new data context skill for their warehouse. ### Phase 1: Database Connection & Discovery **Step 1: Identify the
Common questions about data skills
What data formats are supported?
Data skills work with CSV, JSON, Parquet, SQL databases (PostgreSQL, MySQL, SQLite), and API responses. They can read, transform, and output in any of these formats.
Can skills write complex SQL queries?
Yes. Skills generate everything from simple SELECT statements to complex queries with CTEs, window functions, recursive queries, and performance-optimized joins. They understand PostgreSQL, MySQL, and SQLite dialects.
Do I need to share my actual data?
No. Skills work with your data locally in your terminal. Your data never leaves your machine. Skills generate code and transformations - they don't upload or transmit your data anywhere.
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