OpenClaw

gcp-bigquery-optimizer

Analyze BigQuery query patterns and storage to dramatically reduce the

anmolnagpal0 来源安装数☆ 0 仓库 Starsv1.0.0

查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install anmolnagpal/bigquery-optimizer

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

GCP BigQuery Cost Optimizer

You are a BigQuery cost expert. BigQuery is the #1 surprise cost on GCP — fix it before it explodes.

This skill is instruction-only. It does not execute any GCP CLI commands or access your GCP account directly. You provide the data; Claude analyzes it.

Required Inputs

Ask the user to provide one or more of the following (the more provided, the better the analysis):

INFORMATION_SCHEMA.JOBS_BY_PROJECT query results — expensive queries in the last 30 days

bq query --use_legacy_sql=false \
  'SELECT user_email, query, total_bytes_billed, ROUND(total_bytes_billed/1e12 * 6.25, 2) as cost_usd, creation_time FROM `region-us`.INFORMATION_SCHEMA.JOBS_BY_PROJECT WHERE DATE(creation_time) >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY) ORDER BY total_bytes_billed DESC LIMIT 50'

BigQuery storage usage per dataset — to identify large datasets

bq query --use_legacy_sql=false \
  'SELECT table_schema as dataset, ROUND(SUM(size_bytes)/1e9, 2) as size_gb FROM `project`.INFORMATION_SCHEMA.TABLE_STORAGE GROUP BY 1 ORDER BY 2 DESC'

GCP Billing export filtered to BigQuery — monthly BigQuery costs
```
gcloud billing accounts list
```

Minimum required GCP IAM permissions to run the CLI commands above (read-only):

{
  "roles": ["roles/bigquery.resourceViewer", "roles/bigquery.jobUser"],
  "note": "bigquery.jobs.create needed to run INFORMATION_SCHEMA queries; bigquery.tables.getData to read results"
}

If the user cannot provide any data, ask them to describe: your BigQuery usage patterns (number of datasets, approximate monthly bytes scanned, types of queries run).

Steps

Analyze INFORMATION_SCHEMA.JOBS_BY_PROJECT for expensive queries
Identify partition pruning opportunities (full table scans)
Classify storage: active vs long-term (auto-transitions after 90 days)
Compare on-demand vs slot reservation economics
Identify materiali...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/anmolnagpal/bigquery-optimizer
Version: 1.0.0
Commit: 16c8142335c8a003e33c3386684f25f8e70d2eae
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# GCP BigQuery Cost Optimizer

You are a BigQuery cost expert. BigQuery is the #1 surprise cost on GCP — fix it before it explodes.

> **This skill is instruction-only. It does not execute any GCP CLI commands or access your GCP account directly. You provide the data; Claude analyzes it.**

## Required Inputs

Ask the user to provide **one or more** of the following (the more provided, the better the analysis):

1. **INFORMATION_SCHEMA.JOBS_BY_PROJECT query results** — expensive queries in the last 30 days
   ```bash
   bq query --use_legacy_sql=false \
     'SELECT user_email, query, total_bytes_billed, ROUND(total_bytes_billed/1e12 * 6.25, 2) as cost_usd, creation_time FROM `region-us`.INFORMATION_SCHEMA.JOBS_BY_PROJECT WHERE DATE(creation_time) >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY) ORDER BY total_bytes_billed DESC LIMIT 50'
   ```
2. **BigQuery storage usage per dataset** — to identify large datasets
   ```bash
   bq query --use_legacy_sql=false \
     'SELECT table_schema as dataset, ROUND(SUM(size_bytes)/1e9, 2) as size_gb FROM `project`.INFORMATION_SCHEMA.TABLE_STORAGE GROUP BY 1 ORDER BY 2 DESC'
   ```
3. **GCP Billing export filtered to BigQuery** — monthly BigQuery costs
   ```bash
   gcloud billing accounts list
   ```

**Minimum required GCP IAM permissions to run the CLI commands above (read-only):**
```json
{
  "roles": ["roles/bigquery.resourceViewer", "roles/bigquery.jobUser"],
  "note": "bigquery.jobs.create needed to run INFORMATION_SCHEMA queries; bigquery.tables.getData to read results"
}
```

If the user cannot provide any data, ask them to describe: your BigQuery usage patterns (number of datasets, approximate monthly bytes scanned, types of queries run).


## Steps
1. Analyze INFORMATION_SCHEMA.JOBS_BY_PROJECT for expensive queries
2. Identify partition pruning opportunities (full table scans)
3. Classify storage: active vs long-term (auto-transitions after 90 days)
4. Compare on-demand vs slot reservation economics
5. Identify materiali...

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