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/bigquery-ai-ml

@d6b9f75
by googlegoogle/skills21k stars
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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.

Use this Skill: https://skilld.dev/gh/google/skills/bigquery-ai-ml

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referencesai_score.md

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BigQuery AI.Score

The AI.SCORE function is commonly used with the ORDER BY clause and works well when you want to rank items. The following are common use cases:

  • Retail: Find the top 5 most negative customer reviews about a product.
  • Hiring: Find the top 10 resumes that appear most qualified for a job post.
  • Customer success: Find the top 20 best customer support interactions.

Syntax Reference

AI.SCORE(
  [ prompt => ] 'PROMPT'
  [, connection_id => 'CONNECTION_ID' ]
  [, endpoint => 'ENDPOINT' ]
)

Input Arguments

Argument Requirement Type Description
prompt Required String/Struct The prompt text or a
: : : : struct/tuple of :
: : : : (data, instruction). :
connection_id Optional String The connection ID to
: : : : use for the LLM. :
endpoint Optional String The model endpoint
: : : : (e.g. :
: : : : 'gemini-2.5-flash'). :

Output Schema

Column Name Type Description
(Scalar Result) FLOAT64 A numerical score representing the degree
: : : to which the data matches the instruction. :

Examples

Rank rows by semantic relevance

SELECT *
FROM `dataset.table`
ORDER BY AI.SCORE(
  (content_column, 'relevance to sports'),
  connection_id => 'my-project.us.my-connection'
) DESC
LIMIT 10;

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub9d

    This skill provides a comprehensive reference for BigQuery's built-in AI and machine learning functions. It includes a security consideration regarding potential indirect prompt injection when processing untrusted data with generative AI functions. These patterns are standard for the intended data analysis use cases and can be managed through proper prompt design and data validation.

  • Socket9d

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  • Snyk9d

    Risk: LOW · No issues

Signed by skilld at d6b9f75. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

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metadata
{
  "version": "1.1.0",
  "category": "AiAndMachineLearning"
}

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