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claude-codedata

Claude-skill-registry data-querying

Write and verify SQL queries with BigQuery. Use when executing bq commands, writing SQL queries, or including query results in documents.

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/data-querying" ~/.claude/skills/majiayu000-claude-skill-registry-data-querying && rm -rf "$T"
manifest: skills/data/data-querying/SKILL.md
tags
#sql#bigquery#data-analysis#query-generation#bq#database
source content

Data Querying

Verification Requirement

All queries MUST be executed with 

bq
and verified before inclusion. Never include unverified queries or fabricated data.

Query Process

  1. Dry run: Validate syntax and check cost

    bq query --project_id=<PROJECT_ID> --use_legacy_sql=false --dry_run "SELECT ..."

    Cost: ~$5/TB. <1GB is light, 2GB+ needs optimization.

  2. Execute: Run and confirm results

    bq query --project_id=<PROJECT_ID> --use_legacy_sql=false --format=csv "SELECT ..."

  3. Learn: Study existing queries in project docs for patterns.

Query Design

  • Specify exact date ranges
  • Filter partitioned tables by partition key
  • Avoid correlated subqueries (use JOINs/CTEs)
  • Filter early with CTEs before joining large tables

Documentation

  1. Execute exact query with 
    bq
  2. Copy real output only
  3. State time period and what query measures