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 commands/yeaight7/agent-powerups/bigquery-cost-checkgit clone --depth 1 https://github.com/yeaight7/agent-powerupsWrote 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/yeaight7/agent-powerups/bigquery-cost-check)<a href="https://agentmods.dev/commands/yeaight7/agent-powerups/bigquery-cost-check"><img src="https://agentmods.dev/badge/commands/yeaight7/agent-powerups/bigquery-cost-check.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 | $0.00019 | $0.00285 |
| Opus 5 | $0.00010 | $0.00143 |
| Sonnet 5 | $0.00004 | $0.00057 |
| Haiku 4.5 | $0.00002 | $0.00028 |
Grade A, and why
bigquery-cost-check 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.
What it actually says
BigQuery Cost Check Command
CRITICAL BEHAVIORAL RULES
- Analyze Static SQL: You cannot run the query to see the bytes billed. You must statically analyze the SQL syntax and dbt
config()blocks. - Focus on Bytes Billed: In BigQuery, cost is driven by data scanned, not compute time. Focus entirely on reducing data scanned.
Execution Steps
- Read the provided SQL or dbt model file.
- Look for the target table's schema (if available in the repo) to identify partitioned columns.
- Evaluate the
WHEREclauses. Are partition keys used? If not, flag a full table scan. - Evaluate the
SELECTclauses. Are there unnecessary columns? - For dbt models, check the
configblock. Is this a table, view, or incremental model? If it's a massive daily table rebuild, recommend an incremental strategy. - Provide a concise report:
- Risk Level: (Low, Medium, High)
- Cost Drivers: (The specific lines or patterns driving cost)
- Recommendations: (Specific SQL or config changes to implement)
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 · 24 lines · 19 tokens per session scan A 3687d6d9337d
bigquery-cost-check is a command published in the GitHub repository yeaight7/agent-powerups (6 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 19 tokens to every session and 285 once invoked, about $0.0001 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 2026-08-31.
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t800-update
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