bigquery-optimizerAnalyze BigQuery query patterns and storage to dramatically reduce the
Install via ClawdBot CLI:
clawdbot install anmolnagpal/bigquery-optimizerGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Mar 22, 2026
A company runs daily reports on sales data stored in BigQuery, scanning terabytes due to unfiltered queries on large transaction tables. This skill helps identify partition pruning opportunities on date-partitioned tables and recommends materialized views for repetitive dashboard queries, reducing monthly costs significantly.
A SaaS provider stores extensive user activity logs in BigQuery for analytics, leading to high costs from ad-hoc queries scanning entire datasets. The skill analyzes storage usage to classify logs as long-term data and suggests auto-transitions, while flagging expensive full-table scans for optimization.
A financial institution uses BigQuery for complex risk analysis queries that involve large joins and aggregations, resulting in unpredictable on-demand costs. This skill evaluates query patterns to recommend slot reservations for consistent performance and identifies query rewrites to reduce bytes billed.
A healthcare organization aggregates patient data from multiple sources into BigQuery, facing high costs from repeated queries on unpartitioned tables. The skill analyzes INFORMATION_SCHEMA data to pinpoint top expensive queries and provides storage optimization tips for managing large datasets efficiently.
Offer monthly subscriptions to businesses for ongoing BigQuery cost analysis and recommendations. Users provide exported query and storage data, and the service delivers regular reports with actionable insights to reduce expenses, targeting companies with significant BigQuery usage.
Provide one-time consulting services to analyze BigQuery usage and implement optimizations, such as query rewrites and storage lifecycle policies. This model appeals to organizations needing hands-on assistance to address specific cost spikes or compliance requirements.
Develop a free version that analyzes limited data samples, with premium features like detailed slot reservation analysis and materialized view recommendations. This model attracts users through self-service optimization and upsells advanced capabilities for larger enterprises.
💬 Integration Tip
Ensure users have read-only IAM permissions to run INFORMATION_SCHEMA queries and export data safely, avoiding direct GCP account access.
Scored Apr 19, 2026
Use the @steipete/oracle CLI to bundle a prompt plus the right files and get a second-model review (API or browser) for debugging, refactors, design checks, or cross-validation.
Local search/indexing CLI (BM25 + vectors + rerank) with MCP mode.
Use when designing database schemas, writing migrations, optimizing SQL queries, fixing N+1 problems, creating indexes, setting up PostgreSQL, configuring EF Core, implementing caching, partitioning tables, or any database performance question.
Connect to Supabase for database operations, vector search, and storage. Use for storing data, running SQL queries, similarity search with pgvector, and managing tables. Triggers on requests involving databases, vector stores, embeddings, or Supabase specifically.
Use SQLite correctly with proper concurrency, pragmas, and type handling.
Write correct MySQL queries avoiding common pitfalls with character sets, indexes, and locking.