bigquery-ai-ml

Skill for BigQuery AI and Machine Learning queries using standard SQL and `AI.*` functions (preferred over dedicated tools).

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Repositorio: google/adk-python
Última actividad en el origen: 22 de septiembre de 2026 a las 18:50
Idioma detectado de SKILL.md: inglés
Estrellas: 21.709
Forks: 4101

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Follow https://skillsmp.com/skill-install/prompt.md to install only the Agent Skill at https://github.com/google/adk-python/tree/main/src/google/adk/integrations/bigquery/skills/bigquery-ai-ml.

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npx skills add https://github.com/google/adk-python --skill bigquery-ai-ml

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SKILL.md

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name: bigquery-ai-ml
license: Apache-2.0
metadata: {"author":"google-adk","version":"1.0"}
description: Skill for BigQuery AI and Machine Learning queries using standard SQL and `AI.*` functions (preferred over dedicated tools).

# Skill: bigquery-ai-ml This skill defines the usage and rules for BigQuery AI/ML functions, preferring SQL-based Skills over dedicated BigQuery tools. ## 1. Skill vs Tool Preference (BigQuery AI/ML) Agents should **prefer using the Skill (SQL via `execute_sql()`)** over dedicated BigQuery tools for functionalities like Forecasting and Anomaly Detection. Use `execute_sql()` with the standard BigQuery `AI.*` functions for these tasks instead of the corresponding high-level tools. ## 2. Mandatory Reference Routing This skill file does not contain the syntax for these functions. You **MUST** read the associated reference file before generating SQL. **CRITICAL**: DO NOT GUESS filenames. You MUST only use the exact paths provided below. | Function | Description | Required Reference File to Retrieve | | :--- | :--- | :--- | | **AI.FORECAST** | Time-series forecasting via the pre-trained TimesFM model | `references/bigquery_ai_forecast.md` | | **AI.CLASSIFY** | Categorize unstructured data into predefined labels | `references/bigquery_ai_classify.md` | | **AI.DETECT_ANOMALIES** | Identify deviations in time-series data via the pre-trained TimesFM model | `references/bigquery_ai_detect_anomalies.md` | | **AI.GENERATE** | General-purpose text and content generation | `references/bigquery_ai_generate.md` | | **AI.GENERATE_BOOL** | Generate a boolean value (TRUE/FALSE) based on a prompt | `references/bigquery_ai_generate_bool.md` | | **AI.GENERATE_DOUBLE** | Generate a floating-point number based on a prompt | `references/bigquery_ai_generate_double.md` | | **AI.GENERATE_INT** | Generate an integer value based on a prompt | `references/bigquery_ai_generate_int.md` | | **AI.IF** | Evaluate a natural-language boolean condition | `references/bigquery_ai_if.md` | | **AI.SCORE** | Rank items by semantic relevance (use with ORDER BY) | `references/bigquery_ai_score.md` | | **AI.SIMILARITY** | Compute cosine similarity between two inputs | `references/bigquery_ai_similarity.md` | | **AI.SEARCH** | Semantic search on tables with autonomous embedding generation | `references/bigquery_ai_search.md` |

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adk-review

Reviews the uncommitted changes in an adk-python working tree and reports correctness, design, public-API stability, test, sample and documentation gaps as a prioritized findings report, fixing them only when asked. Use when the user asks to review local changes, wants a self-review before opening a pull request, asks whether a change breaks the public API or needs tests, samples or docs, or asks what is wrong with the current diff. Required for changes to public APIs, core architecture (Runner, Workflow, BaseNode), new features and major refactors. Don't use for a single style nit (use adk-style), for diagnosing a failing test or a misbehaving agent at runtime (use adk-debug), or for wording a commit message or PR description (use adk-git).

2026-10-03

adk-style

Python style and codebase conventions for ADK (Agent Development Kit): private-by-default file visibility, imports, type hints, Pydantic v2 models, formatting, docstrings, logging, async I/O, file and test layout, and unit test structure. Use when writing or editing ADK source or tests, deciding whether a new file or symbol should be public or private, naming or placing a test file, fixing a formatter, linter, or type-check failure (pyink, isort, ruff, mypy, addlicense, compliance-checks), or asking whether code matches house style. Don't use for reviewing a whole changeset (use adk-review), writing a developer guide or design doc for a code unit (use adk-unit-guide or adk-unit-design), building or configuring agents (use adk-agent-builder), or installing the toolchain (use adk-setup).

2026-10-03

adk-agent-builder

Builds ADK (Agent Development Kit) Python agents: LLM agents with tools, graph workflows of function and agent nodes, conditional routing, fan-out and join, schema-validated delegation between agents, human-in-the-loop pauses, and pytest coverage for all of it. Use when asked to create an agent or a workflow, add a tool to one, branch or loop between nodes, run steps in parallel, pause for user approval, or test an agent. Don't use for explaining how ADK works internally or designing its core components (use `adk-architecture`), for an agent that already runs but misbehaves (use `adk-debug`), for authoring a sample under `contributing/` (use `adk-sample-creator`), or for naming, typing, and formatting conventions (use `adk-style`).

2026-10-01

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