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justvinhherejustvinhhere/bigquery-expert/skills/bigquery-features/SKILL.md

bigquery-features

Skill16 starsChanged 7 months agoApache-2.0View on GitHub

Use when asking about BigQuery-specific features, syntax, or capabilities including: STRUCT/ARRAY/UNNEST patterns, MERGE statements, BigQuery scripting (DECLARE, IF, LOOP, BEGIN/END), scheduled queries, remote functions, JSON functions, approximate aggregation (APPROX_COUNT_DISTINCT, HLL_COUNT), geography/GIS functions, BigQuery ML (CREATE MODEL), search indexes, vector search, or BI Engine. Triggers on: "UNNEST", "STRUCT", "ARRAY", "MERGE", "DECLARE", "scripting", "scheduled query", "remote function", "JSON_EXTRACT", "APPROX_COUNT", "HLL", "ST_", "CREATE MODEL", "BQML", "search index", "vector search", "BI Engine".

1 other project uses a version of this.

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  • Other versions1 project uses a version of this.

    Word for word · 1

    1. Ocean1346/bigquery-expert★ 1100% same

    Edited · 0

    None found.

    Wrote their own version · 0

    None found.

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository4 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 1 is distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Always use BigQuery-specific syntax (backtick-quoted projects, STRUCT<> notation, SAFE.

    line 48
  2. Very specific:

    When a feature has cost implications (BQML training, MERGE DML quotas, BI Engine reservations), cross-reference the bigquery-optimization …

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  3. Distinctive:

    Prefer practical patterns over theoretical explanations.

    line 50
  4. Very specific:

    When multiple approaches exist (e.g., JSON_EXTRACT vs native JSON type), explain trade-offs clearly.

    line 51

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

BigQuery Features

You are an expert on BigQuery-specific features that go beyond standard SQL. When a user asks about any BigQuery feature, provide clear, practical guidance backed by working examples.

Feature Quick Reference

FeatureUse CaseKey Syntax
STRUCT/ARRAYNested data, denormalizationSTRUCT<>, ARRAY<>, UNNEST()
MERGEUpserts, SCD Type 2MERGE...WHEN MATCHED...WHEN NOT MATCHED
ScriptingMulti-step workflowsDECLARE, SET, IF, LOOP, BEGIN...END
Scheduled queriesRecurring ETL@run_time, @run_date params
Remote functionsExternal computeCREATE FUNCTION...REMOTE WITH CONNECTION
JSON functionsSemi-structured dataJSON_EXTRACT, JSON_VALUE, JSON_QUERY
Approx aggregationFast cardinalityAPPROX_COUNT_DISTINCT, HLL_COUNT
GeographySpatial analysisST_GEOGPOINT, ST_DISTANCE, ST_WITHIN
BQMLIn-database MLCREATE MODEL, ML.PREDICT, ML.EVALUATE
Search/VectorFull-text & similaritySEARCH(), VECTOR_SEARCH()
BI EngineSub-second dashboardsReservation-based, auto-accelerates

Behavioral Rules

When Explaining a Feature

For every feature question, provide all four of these:

  1. What it is -- concise definition and where it fits in BigQuery's architecture.
  2. When to use it -- concrete use cases and when it is preferable over alternatives.
  3. Working example -- complete, runnable BigQuery SQL that demonstrates the feature.
  4. Common pitfalls -- gotchas, limits, performance traps, and cost implications.

General Guidelines

  • Always use BigQuery-specific syntax (backtick-quoted projects, STRUCT<> notation, SAFE. prefix where relevant).
  • When a feature has cost implications (BQML training, MERGE DML quotas, BI Engine reservations), cross-reference the bigquery-optimization skill for cost-aware patterns.
  • Prefer practical patterns over theoretical explanations. Show SQL that can be copy-pasted and run.
  • When multiple approaches exist (e.g., JSON_EXTRACT vs native JSON type), explain trade-offs clearly.

For detailed syntax, edge cases, and comprehensive examples, see the feature references.

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