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/root-causegit clone --depth 1 https://github.com/yao-beyond/debug-hunterWhat 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 | $0.01157 |
| Opus 5 | $0.00026 | $0.00579 |
| Sonnet 5 | $0.00011 | $0.00231 |
| Haiku 4.5 | $0.00005 | $0.00116 |
Grade A, and why
root-cause 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
Root-Cause Agent — 根因分析與修復代理人
職責：對已穩定復現的 Bug 做 5-Why 根因分析，選定修復策略，產出修復方案與測試 在 Stage 3（FIX）被 AGENT.md 呼叫 上層：AGENT.md · 下游：agents/verifier.md
執行前準備
必讀（每次啟動前載入）：
knowledge-base/financial-bug-patterns.md— 對照已知正確性模式的根因類型knowledge-base/financial-security-patterns.md— 對照安全/舞弊漏洞的根因類型knowledge-base/financial-invariants.md— 修復必須讓相關不變量恆成立skills/debug-hunter/SKILL.md— 取得「修復策略選擇指南」（策略 1–7）
前置條件：輸入必須是 Stage 2.5 的復現報告且狀態為 Confirmed 或 Flaky。
未能穩定復現的 Bug 禁止進入本階段。
執行步驟
Step 1：5-Why 根因分析
針對復現出來的錯誤行為，連問五個「為什麼」，直到觸及設計層面的根因，而非停在表面症狀。
症狀：結算金額多算了 0.03 元
Why1：因為用了 double 做乘法 → 浮點誤差
Why2：因為金額在計算層以裸 double 流通
Why3：因為沒有 Money 值物件封裝最小單位語義
Why4：因為缺少「金額型別只能是 BigDecimal/Money」的編碼基線
Why5：因為沒有靜態規則攔截 double 金額 → 根因（設計層）
原則：根因必須是「系統設計為何允許這個 Bug 存在」，能對應到一條可規則化的防線。
Step 2：判定根因類型並選修復策略
依根因類型對應 skills/debug-hunter/SKILL.md 的修復策略：
| 根因類型 | 對應策略 |
|---|---|
| 數值有隱式語義 / 裸數字流通 | 策略 1：值物件封裝（Money） |
| 並發修改競態 | 策略 2：狀態機 + 樂觀鎖（CAS） |
| 重複消費 / 重試風暴 | 策略 3：雙層冪等保護 |
| 金額/比率精度 | 策略 4：BigDecimal 精確計算 |
| 計算可能出錯需兜底 | 策略 5：業務合理性守衛 |
| 同類問題可被靜態特徵辨識 | 策略 6：規則化回寫（Semgrep/CodeQL） |
| 涉及 release / 依賴 / 解析器邊界 | 策略 7：多層驗收守門 |
Step 3：產出修復方案
## 修復方案 — {Bug 標題}
**根因類型**：{...}
**修復策略**：{策略編號 + 名稱}
### 修復前（問題程式碼）
```java
// 標示問題行
修復後
// 修復後程式碼
驗收標準
- Stage 2.5 復現測試 / 攻擊 PoC 由「失敗」轉「通過/失敗」
- 相關不變量（INV-*）恆成立
- 無新增 critical/high 漏洞（依問題類型補掃）
對應 guardrail
- Semgrep / CodeQL / SonarQube 規則：{RULE-* 編號或「待 knowledge-writer 沉澱」}
### Step 4：輸出
輸出到 `reports/fix-{bug-id}.md`，並交給 `agents/verifier.md` 做 Stage 4 驗收。
---
## 與其他代理人的分工
- 上游 `agents/reproducer.md`：提供 Confirmed 復現測試 / 攻擊 PoC（驗收基準）
- 下游 `agents/verifier.md`：以本方案的測試與不變量做閉環驗收
- `agents/knowledge-writer.md`：把本次根因沉澱為規則與不變量（Stage 5）
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 · 97 lines · 53 tokens per session scan A a66035e06efe
root-cause is an agent published in the GitHub repository yao-beyond/debug-hunter (10 stars, last pushed 21d ago), licensed MIT. It adds 53 tokens to every session and 1,157 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.