Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/justvinhhere/bigquery-expertWrote 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/commands/justvinhhere/bigquery-expert/bq-optimize)<a href="https://agentmods.dev/commands/justvinhhere/bigquery-expert/bq-optimize"><img src="https://agentmods.dev/badge/commands/justvinhhere/bigquery-expert/bq-optimize/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/justvinhhere/bigquery-expert/bq-optimize"><img src="https://agentmods.dev/badge/commands/justvinhhere/bigquery-expert/bq-optimize.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00021 | $0.00333 |
| Opus 5.5 | $0.00008 | $0.00133 |
| Sonnet 5.5 | $0.00004 | $0.00067 |
| Haiku 4.5 | $0.00002 | $0.00033 |
Grade A, and why
bq-optimize 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 1mo 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.
What it actually says
BigQuery SQL Optimize
Rewrite the provided BigQuery SQL with all detected anti-patterns fixed, using the bigquery-optimization skill.
Instructions
-
Determine the SQL to optimize:
- If a file path argument is provided, read that file.
- If no argument is provided, look for the most recent BigQuery SQL in the current conversation.
- If no SQL is found, ask the user to provide a query or file path.
-
Detect all anti-patterns by running the full 11-pattern check.
-
Apply all fixes to produce an optimized version of the query:
- Preserve the original query semantics exactly -- the optimized query must return the same data.
- Apply fixes in this order: SimpleSelectStar, SemiJoinWithoutAgg, DynamicPredicate, OrderByWithoutLimit, StringComparison, CTEsEvalMultipleTimes, LatestRecordWithAnalyticFun, JoinOrder, WhereOrder, MissingDropStatement, ConvertTableToTemp.
-
Output the result:
## Optimized Query
(fully rewritten SQL)
## Changes Applied
1. **PatternName**: What was changed and why.
2. **PatternName**: What was changed and why.
## Summary
X anti-pattern(s) fixed. The optimized query preserves the original semantics.
- If no anti-patterns are found, return the original query and confirm it already follows best practices.
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.
- 1mo ago First seen · 42 lines · 21 tokens per session scan A a1ac55b5a8da
bq-optimize is a command published in the GitHub repository justvinhhere/bigquery-expert (17 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 21 tokens to every session and 333 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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setup-bigquery
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review-epo-claims
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database-setup
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new-migration
Scaffold a new database migration file pair (up + down) with auto-detection of migration tool and numbering.