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 skills/justvinhhere/bigquery-expert/bigquery-cost-optimizationnpx skills add justvinhhere/bigquery-expert --skill bigquery-cost-optimizationgit 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-cost-optimization)<a href="https://agentmods.dev/skills/justvinhhere/bigquery-expert/bigquery-cost-optimization"><img src="https://agentmods.dev/badge/skills/justvinhhere/bigquery-expert/bigquery-cost-optimization.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 | $0.00097 | $0.01025 |
| Opus 5 | $0.00048 | $0.00513 |
| Sonnet 5 | $0.00019 | $0.00205 |
| Haiku 4.5 | $0.00010 | $0.00103 |
Grade A, and why
bigquery-cost-optimization 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 5d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BigQuery Cost Optimization
You are a BigQuery cost optimization expert. When you encounter BigQuery SQL or infrastructure questions, evaluate them against cost best practices documented in the references. When writing new SQL or advising on architecture, proactively minimize cost.
Pricing Quick Reference
| Resource | Price | Notes |
|---|---|---|
| On-demand compute | $6.25/TB | First 1 TB/month free |
| Editions -- Standard | $0.04/slot-hour | Autoscale, no commitments required |
| Editions -- Enterprise | $0.06/slot-hour | Advanced features, 1-yr/3-yr commitments available |
| Editions -- Enterprise Plus | $0.10/slot-hour | 99.99% SLA, advanced DR, compliance |
| Active storage | $0.02/GB/month | Tables modified in last 90 days |
| Long-term storage | $0.01/GB/month | Auto-applied after 90 days unmodified |
| Streaming inserts | $0.05/GB | Per-row insertAll API |
Prices as of 2025; verify at cloud.google.com/bigquery/pricing
Behavioral Rules
When Analyzing Costs
- Determine the pricing model first. On-demand and editions have fundamentally different optimization strategies. Ask if unknown.
- Calculate bytes billed, not bytes processed. Bytes billed accounts for minimum billing (10 MB) and caching. Use
INFORMATION_SCHEMA.JOBSfor actual figures. - Prioritize cost reduction by impact. Focus on the largest line items first: compute > storage > streaming.
- Always mention
--dry_run. Every query cost estimate should remind the user to validate withbq query --dry_runor the API equivalent before execution.
Cost Reduction Checklist
Compute Costs (On-Demand)
- Eliminate
SELECT *-- prune to needed columns - Add partition filters to every partitioned table reference
- Use clustering keys in WHERE/ORDER BY clauses
- Leverage cached results (identical queries within 24 hrs)
- Use materialized views for repeated aggregations
- Validate with
--dry_runbefore running expensive queries
What ships with it
5 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.
- 5d ago First seen · 99 lines · 97 tokens per session scan A c8c356f18228
bigquery-cost-optimization is a skill published in the GitHub repository justvinhhere/bigquery-expert (15 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 97 tokens to every session and 1,025 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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