prompt02_agent

prompt02_agent is a cursor rule for Cursor from mercari/sample-bigquery-ai-coding. It costs 0 tokens per session (275 once invoked), scanned A, original, MIT.

A Cursor rule containing a Japanese-language procedure for analysing gross merchandise value, or the total value of goods sold. It describes Google Cloud login, a BigQuery query, and review of the results.

In plain words
What is it for?
Use it to authenticate with Google Cloud, run the repository's category-level GMV query for the past three years, and explain the main increases and decreases.
Why use it?
It gives an agent a fixed sequence for reproducing this specific analysis instead of leaving the authentication, query, and review steps implicit.

Cursor rule for Cursor

Written for Cursor: installed under .cursor/.

Good fit Use it to authenticate with Google Cloud, run the repository's category-level GMV query for the past three years, and explain the main increases and decreases.

Compare 6 cursor rules from other repositories ↓
Install with agentmods
npx agentmods add rules/mercari/sample-bigquery-ai-coding/prompt02_agent
Install

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.

Clone the repo
git clone --depth 1 https://github.com/mercari/sample-bigquery-ai-coding

Made for: Cursor.

Wrote 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.

agentmods badge for prompt02_agent

README.md
[![agentmods](https://agentmods.dev/badge/rules/mercari/sample-bigquery-ai-coding/prompt02_agent/github.svg)](https://agentmods.dev/rules/mercari/sample-bigquery-ai-coding/prompt02_agent)
Your own site
<a href="https://agentmods.dev/rules/mercari/sample-bigquery-ai-coding/prompt02_agent"><img src="https://agentmods.dev/badge/rules/mercari/sample-bigquery-ai-coding/prompt02_agent/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for prompt02_agent

Your own site · 80×15
<a href="https://agentmods.dev/rules/mercari/sample-bigquery-ai-coding/prompt02_agent"><img src="https://agentmods.dev/badge/rules/mercari/sample-bigquery-ai-coding/prompt02_agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Nothing until a file matches its globs; then the whole rule loads.
When invoked 275 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.00275
Opus 5.5 $0.00000 $0.00110
Sonnet 5.5 $0.00000 $0.00055
Haiku 4.5 $0.00000 $0.00028

Measured 1mo ago against content hash cca368fd847e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 1mo 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.

.cursor/rules/prompt02_agent.mdc · 30 lines

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。

Changes

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.

  1. 1mo ago First seen · 30 lines · 0 tokens per session scan A cca368fd847e

Subscribe to this mod's changes

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.