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 rules/mercari/sample-bigquery-ai-coding/prompt02_agentgit clone --depth 1 https://github.com/mercari/sample-bigquery-ai-codingWhat 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 | $0.00000 | $0.00275 |
| Opus 5 | $0.00000 | $0.00138 |
| Sonnet 5 | $0.00000 | $0.00055 |
| Haiku 4.5 | $0.00000 | $0.00028 |
Grade A, and why
prompt02_agent 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 2d 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
GMV分析：ワークフロー再現プロンプト
クエリは、過去3年間のカテゴリ別GMVを集計します。 過去3年間のGMVトレンドを分析するために、以下の手順に従ってください。
1. Google Cloud認証
# ブラウザで認証を実行します
gcloud auth login
2. BigQueryクエリの実行
# リポジトリルートに移動します
cd $(git rev-parse --show-toplevel)
# CSV出力形式でクエリを実行します
bq query --use_legacy_sql=false --format=csv \
< queries/query03_base.sql
注：モデルがターミナルで全出力を確認する必要があるため、CSVファイルには保存しないでください。
3. 分析
すべての結果を確認し、過去3年間のGMVトレンドを分析し、増減の主な理由を箇条書きでリストアップしてください。
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.
- 2d ago First seen · 30 lines · 0 tokens per session scan A cca368fd847e
prompt02_agent is a cursor rule published in the GitHub repository mercari/sample-bigquery-ai-coding (5 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 275 tokens. 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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