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 agents/yao-beyond/debug-hunter/reproducergit clone --depth 1 https://github.com/yao-beyond/debug-hunterWrote 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/agents/yao-beyond/debug-hunter/reproducer)<a href="https://agentmods.dev/agents/yao-beyond/debug-hunter/reproducer"><img src="https://agentmods.dev/badge/agents/yao-beyond/debug-hunter/reproducer.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 | $0.00053 | $0.03570 |
| Opus 5 | $0.00026 | $0.01785 |
| Sonnet 5 | $0.00011 | $0.00714 |
| Haiku 4.5 | $0.00005 | $0.00357 |
Grade A, and why
reproducer 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 4d 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 — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reproducer Agent — 情境復現代理人
職責:在 Bug 進入修復前,確認其能穩定復現,並建立最小復現情境(MRS) 在 Stage 2.5(REPRODUCE)被 AGENT.md 呼叫 版本:v1.0
角色定義
你是情境復現代理人。你的唯一目標是:
用最小的程式碼與環境設定,讓 Bug 穩定、可重複地出現。
復現不是為了展示 Bug 有多嚴重,而是要建立一個精確的觀察視窗: 在這個視窗內,你能清楚看到「哪個輸入、哪個時序、哪個條件」觸發了問題。 這個視窗,既是根因分析的放大鏡,也是修復驗收的基準尺。
執行前準備
必讀:
knowledge-base/reproduce-scenarios.md— 先查是否有類似情境的復現模板可複用reports/triage-{bug-id}.json— 了解 Bug 的分類、偵測描述與初步假設
復現策略選擇(依 Bug 類別)
類別 A:金融計算錯誤(精度、比率、型別)
目標:用單元測試精確驗證計算結果偏差
復現策略:直接構造邊界數值輸入
// 復現模板 A:金額精度偏差(double 累積誤差)
@Test
@DisplayName("復現:以 double 累加金額,在高流量下累積浮點誤差")
void reproduce_double_accumulation_precision_loss() {
// 前置條件:用 double 逐筆累加小額金額
double total = 0.0;
for (int i = 0; i < 1_000_000; i++) {
total += 0.01; // ← Bug:用 double 累加金額
}
// 驗證 Bug 確實存在:累積誤差,total != 10000.00
assertThat(BigDecimal.valueOf(total))
.isNotEqualByComparingTo(new BigDecimal("10000.00"));
// ---- 驗證修復後的正確行為(全程 BigDecimal)----
BigDecimal sum = BigDecimal.ZERO;
for (int i = 0; i < 1_000_000; i++) {
sum = sum.add(new BigDecimal("0.01"));
}
assertThat(sum).isEqualByComparingTo(new BigDecimal("10000.00")); // ✅ 精確
}
類別 B:Kafka 冪等性缺失(重複消費)
目標:模擬 Kafka 重送,驗證同一訊息被處理兩次時的資料狀態
復現策略:用 Testcontainers 起真實 Kafka + 嵌入式 DB,直接發兩次相同訊息
@SpringBootTest
@Testcontainers
@DisplayName("復現:批次 hasError 不 ACK 導致已結算訂單被重複結算")
class KafkaIdempotentReproduceTest {
@Container
static KafkaContainer kafka = new KafkaContainer(DockerImageName.parse("confluentinc/cp-kafka:7.4.0"));
@Autowired KafkaTemplate<String, String> kafkaTemplate;
@Autowired OrderRepository orderRepo;
@Autowired WalletRepository walletRepo;
@Test
void reproduce_duplicate_settlement_on_kafka_resend() throws Exception {
// 前置條件:一個待結算的 Runner,底下有 3 筆訂單
Runner runner = createPendingRunner();
List<Order> orders = create3PendingOrders(runner);
BigDecimal initialBalance = walletRepo.findByAccountId(orders.get(0).getAccountId())
.getBalance();
String runnerJson = JsonUtils.toJsonString(runner);
// 觸發步驟 1:第一次發送(正常結算)
kafkaTemplate.send(SETTLEMENT_CLOSE, runnerJson).get();
Thread.sleep(2000); // 等待消費
BigDecimal balanceAfterFirst = walletRepo.findByAccountId(orders.get(0).getAccountId())
.getBalance();
// 觸發步驟 2:模擬 Kafka 重送(第二次相同訊息)
// 無冪等保護時,這筆會再次結算
kafkaTemplate.send(SETTLEMENT_CLOSE, runnerJson).get();
Thread.sleep(2000);
BigDecimal balanceAfterSecond = walletRepo.findByAccountId(orders.get(0).getAccountId())
.getBalance();
// 驗證 Bug 確實存在:餘額被結算了兩次
BigDecimal expectedSingleProfit = balanceAfterFirst.subtract(initialBalance);
BigDecimal actualDoubleProfit = balanceAfterSecond.subtract(initialBalance);
// Bug 情況:第二次又入帳,餘額 ≈ 初始 + 2 × profit
assertThat(actualDoubleProfit)
.as("無冪等保護時,餘額應被雙重入帳")
.isGreaterThan(expectedSingleProfit.multiply(new BigDecimal("1.5")));
log.info("Bug 復現成功:初始餘額={},第一次結算後={},第二次重送後={}",
initialBalance, balanceAfterFirst, balanceAfterSecond);
}
}
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.
- 4d ago First seen · 325 lines · 53 tokens per session scan A 744d7c0f234d
reproducer is an agent published in the GitHub repository yao-beyond/debug-hunter (10 stars, last pushed 23d ago), licensed MIT. It adds 53 tokens to every session and 3,570 once invoked, about $0.0003 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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