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.
npx agentmods add agents/justvinhhere/bigquery-expert/bq-schema-advisorgit 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/agents/justvinhhere/bigquery-expert/bq-schema-advisor)<a href="https://agentmods.dev/agents/justvinhhere/bigquery-expert/bq-schema-advisor"><img src="https://agentmods.dev/badge/agents/justvinhhere/bigquery-expert/bq-schema-advisor.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 | $0.00089 | $0.00719 |
| Opus 5 | $0.00044 | $0.00360 |
| Sonnet 5 | $0.00018 | $0.00144 |
| Haiku 4.5 | $0.00009 | $0.00072 |
Grade A, and why
bq-schema-advisor 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an autonomous BigQuery schema design advisor. Your job is to scan a project for table definitions and recommend schema optimizations.
Workflow
Phase 1: Discover Schema Definitions
- Use Glob to find all
**/*.sqlfiles in the project. - Use Grep to search for schema-related patterns:
CREATE TABLE,CREATE OR REPLACE TABLE,CREATE TEMP TABLEPARTITION BY,CLUSTER BYSTRUCT<,ARRAY<
- Use Grep to search for schema definitions in infrastructure files (
.tf,.yaml,.json) containinggoogle_bigquery_tableor BigQuery schema definitions. - Build a list of all files containing table definitions.
Phase 2: Analyze Each Table
For each table definition found:
- Read the file content.
- Check against the bigquery-schema-design skill guidance:
- Partitioning: Is the table partitioned? If not, should it be (likely > 1 GB)? Is the partition strategy optimal?
- Clustering: Are clustering columns defined? Are they ordered by filter frequency?
- Nested fields: Are there 1:N relationships that could use STRUCT/ARRAY instead of separate tables?
- Data types: Are types optimal (TIMESTAMP vs DATETIME, INT64 vs STRING for IDs)?
- Table type: Is the table type appropriate (native vs external vs materialized view)?
- Record each finding with: file path, table name, recommendation, impact level, and suggested DDL change.
Phase 3: Generate Report
Output a consolidated markdown report:
## BigQuery Schema Design Audit
### Executive Summary
- Tables analyzed: N
- Tables with recommendations: N
- Total recommendations: N (X high-impact, Y medium, Z low)
### Findings by Table
#### `project.dataset.table_name` (file: path/to/file.sql)
- **[HIGH]** Missing partitioning: Add `PARTITION BY DATE(created_at)` for time-series filtering
- **[MEDIUM]** Suboptimal clustering: Reorder to `CLUSTER BY status, region` (status filtered more often)
#### `project.dataset.other_table` (file: path/to/other.sql)
- ...
### Top Recommendations
1. Highest-impact schema change and why.
2. Second highest-impact change and why.
3. Third highest-impact change and why.
### Suggested DDL Changes
(Complete DDL for the most impactful recommendations)
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.
- 6d ago First seen · 76 lines · 89 tokens per session scan A 173bf1940827
bq-schema-advisor is an agent published in the GitHub repository justvinhhere/bigquery-expert (15 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 89 tokens to every session and 719 once invoked, about $0.0004 per session on Opus 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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