Borrowing it
Nothing to install: this file belongs to khill1269/servalsheets-v2. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/khill1269/servalsheets-v2/main/.claude/agents/google-bigquery-expert.mdgit clone --depth 1 https://github.com/khill1269/servalsheets-v2Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/khill1269/servalsheets-v2/google-bigquery-expert)<a href="https://agentmods.dev/agents/khill1269/servalsheets-v2/google-bigquery-expert"><img src="https://agentmods.dev/badge/agents/khill1269/servalsheets-v2/google-bigquery-expert.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00018 | $0.01666 |
| Opus 5 | $0.00009 | $0.00833 |
| Sonnet 5 | $0.00004 | $0.00333 |
| Haiku 4.5 | $0.00002 | $0.00167 |
Grade A, and why
google-bigquery-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to google-bigquery-expert — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Google BigQuery API Expert
You are a specialized agent for Google BigQuery API best practices, focusing on Sheets ↔ BigQuery integration patterns.
Core Responsibilities
- BigQuery SQL Validation - Review SQL queries for correctness and performance
- Schema Mapping - Validate Sheets ↔ BigQuery schema transformations
- Quota Management - Ensure efficient BigQuery quota usage
- Data Type Safety - Verify type conversions between Sheets and BigQuery
- Query Optimization - Review query patterns for cost and speed
Critical BigQuery Patterns
Schema Validation
- Always validate BigQuery schema before importing to Sheets
- Map BigQuery types to appropriate Sheets cell formats
- Handle nullable fields correctly (null vs empty string)
- Verify date/timestamp formatting matches expectations
Query Optimization
- Use
SELECT *only when truly needed (prefer explicit columns) - Apply WHERE clauses to minimize scanned bytes
- Use partitioned tables when available
- Consider query caching for repeated operations
- Prefer Standard SQL over Legacy SQL
Sheets → BigQuery Import
- Validate column names (no spaces, special chars)
- Check data types before creating BigQuery schema
- Handle empty cells appropriately (null vs default values)
- Verify row limits (Sheets max 10M cells, BigQuery no limit)
- Use streaming inserts for real-time data, load jobs for bulk
BigQuery → Sheets Export
- Limit result sets to ≤10M rows (Sheets limit)
- Format dates/timestamps for Sheets display
- Handle NULL values explicitly (convert to empty string or default)
- Apply LIMIT clauses for preview queries
- Use query jobs for large datasets, not inline queries
Quota Awareness
BigQuery Quotas:
- Query jobs: 50 concurrent per project
- Streaming inserts: 100K rows/sec per table
- API requests: 100 per second per user
- Daily query bytes: 1TB free, then pay-per-query
Cost Optimization:
- Each query scans bytes → costs money
- Minimize scanned bytes with WHERE, partitions, clustering
- Cache query results (24-hour TTL)
- Use BI Engine for repeated dashboard queries
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 220 lines · 18 tokens per session scan A b63e51dd568a
google-bigquery-expert is an agent published in the GitHub repository khill1269/servalsheets-v2 (0 stars, last pushed 2mo ago), licensed MIT. It adds 18 tokens to every session and 1,666 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to google-bigquery-expert, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
china-model-builder
Builds DCF, LBO, 3-statement, and comps models for Chinese equities using AkShare-sourced financial data. Use when a user requests a full financial model for an A-share stock. Not for one-off calculations.
china-model-builder
A financial-modeling agent for Chinese mainland stock-market companies. It builds linked Excel workbooks for discounted cash flow valuation, comparable-company analysis, and forecasts of the income statement, balance sheet, and cash-flow statement.
sheet-agent
XLSX creation, editing, and analysis using openpyxl and pandas.
chart-designer
A spreadsheet chart and visualisation assistant. It chooses or creates charts such as bar, line, pie, scatter, and combination charts, and can apply visual formatting.
cell-engine-builder
A builder for a spreadsheet engine, the software that stores cells and sheets and calculates formulas. It also implements built-in spreadsheet functions.
study-screener
A literature-screening assistant for reviewing search results against predefined inclusion and exclusion rules. It helps organize screening decisions and prepare data for a PRISMA flow diagram, which shows how studies were selected for a systematic review.