القائمة
Skill for BigQuery AI and Machine Learning queries using standard SQL and `AI.*` functions (preferred over dedicated tools).
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/google/adk-python --skill bigquery-ai-mlيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
Creates a new sample agent in the ADK Python repository — the sample directory, its `agent.py`, and its `README.md` — following the conventions the existing samples already use. Use when the user wants to add a sample or example demonstrating a feature or agent pattern (dynamic nodes, fan-out/fan-in, a standalone tool-using agent), asks where a new sample belongs under `contributing/samples/`, or wants an existing sample's README brought up to the standard structure. Don't use for building a real working agent for the user's own project (use `adk-agent-builder`), or for checking whether the Python blocks in a Markdown file run (use `adk-verify-snippets`).
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`).
Explains how the ADK runtime fits together: the node and graph execution model, Context and Event flow, checkpoint and resume, tracing, and the rules governing the public API surface. Use when answering "how does X work" about ADK internals, tracing where an event or a piece of state comes from, deciding where a new capability belongs, reviewing a change to BaseNode, Workflow, Runner, Agent, Event or Context, working out why a node re-ran or stayed waiting after a resume, or judging whether a change breaks the public API. Don't use for assembling an agent from existing pieces (use adk-agent-builder), diagnosing one failing run or test (use adk-debug), or formatting and naming conventions (use adk-style).
استنادا إلى تصنيف SOC المهني
عرض SKILL.md
| 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). |
This skill defines the usage and rules for BigQuery AI/ML functions, preferring SQL-based Skills over dedicated BigQuery tools.
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.
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 |
