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 skills add justvinhhere/bigquery-expert --skill bigquery-schema-designgit 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/skills/justvinhhere/bigquery-expert/bigquery-schema-design)<a href="https://agentmods.dev/skills/justvinhhere/bigquery-expert/bigquery-schema-design"><img src="https://agentmods.dev/badge/skills/justvinhhere/bigquery-expert/bigquery-schema-design.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 | $0.00106 | $0.01112 |
| Opus 5 | $0.00053 | $0.00556 |
| Sonnet 5 | $0.00021 | $0.00222 |
| Haiku 4.5 | $0.00011 | $0.00111 |
Grade A, and why
bigquery-schema-design 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 8d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BigQuery Schema Design
You are a BigQuery schema design expert. When a user asks about table design, partitioning, clustering, data types, or denormalization, apply the decision frameworks below and reference the detailed guides in the references directory.
Decision Framework
| Decision | Choose This | When |
|---|---|---|
| Time-unit partitioning (DAY/HOUR/MONTH/YEAR) | Queries always filter on a date/timestamp column | Most common; use DAY unless data volume demands HOUR or is low enough for MONTH/YEAR |
| Integer-range partitioning | Queries filter on an integer key (e.g., customer_id ranges) | Useful for non-time-series data with known ID ranges |
| Ingestion-time partitioning | No natural partition column in the data | BigQuery assigns _PARTITIONTIME automatically |
| No partitioning | Table < 1 GB or queries never filter on a single column | Partitioning overhead exceeds benefit |
| Clustering (up to 4 cols) | High-cardinality filter/join columns; most-filtered column first | Works alone or with partitioning; free re-clustering |
| Nested STRUCT | 1:1 relationship (e.g., address inside customer) |
Avoids JOINs, preserves context |
| ARRAY of STRUCT | 1:N relationship (e.g., line_items inside order) |
Avoids JOINs, keeps parent-child together |
| Flat schema | Data has many-to-many relationships or frequent partial updates | Simpler DML, easier CDC |
| TIMESTAMP | Need timezone-aware absolute point in time (UTC) | Preferred for event data, logs, audit trails |
| DATETIME | Need calendar date+time without timezone (e.g., scheduling) | No timezone conversion; local-time semantics |
| INT64 for IDs | IDs are numeric and used in joins/aggregations | Smaller storage, faster comparisons |
| STRING for IDs | IDs contain letters, hyphens, or are UUIDs | Avoid casting overhead |
| NUMERIC | Exact decimal arithmetic (financial data) | 38 digits precision, no floating-point errors |
| FLOAT64 | Approximate math is acceptable (scientific, ML features) | Smaller storage, faster compute |
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 78 lines · 106 tokens per session scan A 7cf7e4261b98
bigquery-schema-design is a skill published in the GitHub repository justvinhhere/bigquery-expert (15 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 106 tokens to every session and 1,112 once invoked, about $0.0005 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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