Databrain Intelligence
infometa/workbuddyskills
DataBrain intelligence data query assistant. An agent skill from infometa/workbuddyskills.
Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics.
Install Bigquery AI ML
$ npx skills add google/skills --skill bigquery-ai-ml -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install google/skills bigquery-ai-ml --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cloud/bigquery-ai-ml .claude/skills/bigquery-ai-ml && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "bigquery-ai-ml" agent skill from https://github.com/google/skills/tree/main/skills/cloud/bigquery-ai-ml into .claude/skills/bigquery-ai-ml/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bigquery-ai-ml", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/google/skills/tree/main/skills/cloud/bigquery-ai-mlType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add google/skills --skill bigquery-ai-ml -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install google/skills bigquery-ai-ml --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/cloud/bigquery-ai-ml .agents/skills/bigquery-ai-ml && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "bigquery-ai-ml" agent skill from https://github.com/google/skills/tree/main/skills/cloud/bigquery-ai-ml into .agents/skills/bigquery-ai-ml/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bigquery-ai-ml", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add google/skills --skill bigquery-ai-ml -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install google/skills bigquery-ai-ml --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/cloud/bigquery-ai-ml .cursor/skills/bigquery-ai-ml && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "bigquery-ai-ml" agent skill from https://github.com/google/skills/tree/main/skills/cloud/bigquery-ai-ml into .cursor/skills/bigquery-ai-ml/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bigquery-ai-ml", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/google/skills.git --path skills/cloud/bigquery-ai-ml--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add google/skills --skill bigquery-ai-ml -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install google/skills bigquery-ai-ml --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/cloud/bigquery-ai-ml .gemini/skills/bigquery-ai-ml && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "bigquery-ai-ml" agent skill from https://github.com/google/skills/tree/main/skills/cloud/bigquery-ai-ml into .gemini/skills/bigquery-ai-ml/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bigquery-ai-ml", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install google/skills bigquery-ai-mlInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add google/skills --skill bigquery-ai-ml -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/cloud/bigquery-ai-ml .github/skills/bigquery-ai-ml && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "bigquery-ai-ml" agent skill from https://github.com/google/skills/tree/main/skills/cloud/bigquery-ai-ml into .github/skills/bigquery-ai-ml/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bigquery-ai-ml", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add google/skills --skill bigquery-ai-ml -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install google/skills bigquery-ai-ml --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/cloud/bigquery-ai-ml .opencode/skills/bigquery-ai-ml && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "bigquery-ai-ml" agent skill from https://github.com/google/skills/tree/main/skills/cloud/bigquery-ai-ml into .opencode/skills/bigquery-ai-ml/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bigquery-ai-ml", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
bigquery-ai-ml- GitHub stars
- 21k
- Token cost
- ~985 tokens
- SKILL.md length
- 198 words
- Files
- 22 (incl. references)
- Skills in repo
- 147
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics.
- You need to write SQL queries that perform time-series forecasting
- SKILL.md covers Reference Directory and Related Skills
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Detect outliers
What it does
Bigquery AI ML is an agent skill from google/skills, published by the product's own GitHub organization. Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or…
Its SKILL.md is about 990 tokens, which your agent loads only when the skill is triggered. The skill folder holds 22 other files, including reference files (for example `references/ai_agg.md`, `references/ai_causal_effect.md` and `references/ai_classify.md`).
It sits in Data & Analytics, covering Forecasting and time series, Data warehousing and SQL. It works with Google BigQuery. The repository describes itself as: Agent Skills for Google products and technologies. The licence is Apache-2.0.
When your agent uses it
- You need to write SQL queries that perform time-series forecasting
- Detect outliers
- Find key drivers
- Perform semantic search
Example prompts
- “Use the bigquery-ai-ml skill to leverage BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics”
- “/bigquery-ai-ml”
What it can do on your machine
Read from SKILL.md and the folder at commit 7d97937. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Bigquery AI ML loads about 985 tokens when it runs, and up to ~23k if it reads all its reference files. Until then it costs about 179 tokens; SKILL.md has 198 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from google/skills at commit 7d97937, republished under its Apache-2.0 licence (© google). 198 words, ~985 tokens.
Download SKILL.mdSave it as
.claude/skills/bigquery-ai-ml/SKILL.md (or your agent's skills folder). This skill also uses 21 other files; get the full folder from GitHub.- name
- bigquery-ai-ml
- description
- Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.
- metadata.version
- 1.1.0
- metadata.category
- AiAndMachineLearning
BigQuery AI & ML
BigQuery integrates with Vertex AI to provide powerful machine learning and
generative AI capabilities directly within SQL queries using built-in functions
like AI.FORECAST, AI.KEY_DRIVERS, AI.DETECT_ANOMALIES, and AI.GENERATE.
Reference Directory
Functions Reference:
- AI.AGG: ai_agg.md - Multi-row semantic aggregation and summarization.
- AI.CAUSAL_EFFECT: ai_causal_effect.md - Quantifies the impact of an intervention on a time series.
- AI.CLASSIFY: ai_classify.md - Classify text.
- AI.DETECT_ANOMALIES: ai_detect_anomalies.md - Detect anomalies.
- AI.EVALUATE: ai_evaluate.md - Evaluate models.
- AI.FORECAST: ai_forecast.md - Time-series forecasting.
- AI.GENERATE: ai_generate.md - Generate text using LLMs.
- AI.GENERATE_EMBEDDING: ai_generate_embedding.md - Generate embeddings.
- AI.GENERATE_TABLE: ai_generate_table.md - Table-valued AI generation.
- AI.IF: ai_if.md - Evaluate semantic conditions.
- AI.KEY_DRIVERS: ai_key_drivers.md - Identifies key drivers, this is a TVF.
- AI.SCORE: ai_score.md - Score data.
- AI.SEARCH: ai_search.md - Semantic search.
- AI.SIMILARITY: ai_similarity.md - Semantic similarity.
- Remote Models: remote_models.md - Working with remote models (Vertex AI).
- CONTRIBUTION_ANALYSIS:
ml_contribution_analysis.md
- Finds contributing factors, key drivers of change. Requires creating a MODEL entity.
- ML.CORRELATION: ml_correlation.md - Calculates correlation between columns, optionally sliced by dimensions.
- ML.DETECT_CHANGE_POINTS: ml_detect_change_points.md - Detects structural breaks or sustained shifts in a time series.
- ML.SEASONALITY: ml_seasonality.md - Extracts seasonal components from a time series.
- ML.TREND: ml_trend.md - Extracts the long-term trend component from a time series.
- VECTOR_SEARCH: vector_search.md - Vector search best practices.
Related Skills
- BigQuery Basics Skill: SKILL.md file for core BigQuery concepts, resource management, CLI, and client libraries.
© google, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 21 other files (references) in skills/cloud/bigquery-ai-ml of google/skills.
- SKILL.md
- references/ai_agg.md
- references/ai_causal_effect.md
- references/ai_classify.md
- references/ai_detect_anomalies.md
- references/ai_evaluate.md
- references/ai_forecast.md
- references/ai_generate.md
- references/ai_generate_embedding.md
- references/ai_generate_table.md
- references/ai_if.md
- references/ai_key_drivers.md
- references/ai_score.md
- references/ai_search.md
- references/ai_similarity.md
- references/ml_contribution_analysis.md
- references/ml_correlation.md
- references/ml_detect_change_points.md
- references/ml_seasonality.md
- references/ml_trend.md
- … and 2 more
Open the folder on GitHubat commit 7d97937
Compare with similar skills
Bigquery AI ML next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Bigquery AI ML this skillgoogle/skills | 21k | — | ~985 | Automated safety check: Pass | Apache-2.0 | |
| Databrain Intelligenceinfometa/workbuddyskills | 344 | — | ~8k | Automated safety check: Pass | None | |
| Find Hypertable Candidatestimescale/pg-aiguide | 1.9k | 1 repos | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Semantic Analystsidequery/sidemantic | 129 | — | ~982 | Automated safety check: Pass | AGPL-3.0 | |
| Analysis Artifactswarpdotdev/oz-skills | 825 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Bigquery Graphgoogle/adk-python | 22k | — | ~4.8k | Automated safety check: Pass | Apache-2.0 |
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Related
Works with
Categories
Questions about Bigquery AI ML
What does Bigquery AI ML do?
Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Bigquery AI ML is an agent skill from google/skills, published by the product's own GitHub organization. Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics.
When should I use Bigquery AI ML?
Bigquery AI ML fits situations like: you need to write SQL queries that perform time-series forecasting; detect outliers; find key drivers; perform semantic search.
How do I install Bigquery AI ML in Claude Code?
Run `npx skills add google/skills --skill bigquery-ai-ml -a claude-code`. Or copy the skill folder (skills/cloud/bigquery-ai-ml in google/skills) into .claude/skills/bigquery-ai-ml in your project. Claude Code loads it when a task matches its description.
How do I install Bigquery AI ML in Codex?
Run `npx skills add google/skills --skill bigquery-ai-ml -a codex`. Or copy the skill folder (skills/cloud/bigquery-ai-ml in google/skills) into .agents/skills/bigquery-ai-ml in your project. Codex loads it when a task matches its description.
Can I use Bigquery AI ML in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add google/skills --skill bigquery-ai-ml -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bigquery-ai-ml, .gemini/skills/bigquery-ai-ml, .github/skills/bigquery-ai-ml and .opencode/skills/bigquery-ai-ml in your project.
What does Bigquery AI ML need to run?
SKILL.md names no scripts, command-line tools or credentials: Bigquery AI ML is instructions for the agent only.
Does Bigquery AI ML access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Bigquery AI ML safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Bigquery AI ML use?
Bigquery AI ML is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Bigquery AI ML use?
About 985 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 22k tokens, read only when the agent opens those files.
What are the alternatives to Bigquery AI ML?
Skills that share tags, products or a category with Bigquery AI ML: Databrain Intelligence (infometa/workbuddyskills, 344 stars), Find Hypertable Candidates (timescale/pg-aiguide, 1.9k stars), Semantic Analyst (sidequery/sidemantic, 129 stars) and Analysis Artifacts (warpdotdev/oz-skills, 825 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Bigquery AI ML?
google (a GitHub organization, an official publisher) maintains it in google/skills, which has 21,032 GitHub stars. The repository holds 147 skills in this directory. The repository was last updated on October 8, 2026.
Source: google/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.