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 skills/sonature-lab/timsquad/tsq-debuggingnpx skills add sonature-lab/timsquad --skill tsq-debugginggit clone --depth 1 https://github.com/sonature-lab/timsquadWrote 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/skills/sonature-lab/timsquad/tsq-debugging)<a href="https://agentmods.dev/skills/sonature-lab/timsquad/tsq-debugging"><img src="https://agentmods.dev/badge/skills/sonature-lab/timsquad/tsq-debugging.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 | $0.00067 | $0.00663 |
| Opus 5 | $0.00034 | $0.00331 |
| Sonnet 5 | $0.00013 | $0.00133 |
| Haiku 4.5 | $0.00007 | $0.00066 |
Grade A, and why
tsq-debugging 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.
What it actually says
Systematic Debugging
체계적 디버깅을 통해 근본 원인(root cause)을 빠르게 찾고 재발을 방지하는 방법론.
Philosophy
- 증상이 아닌 근본 원인을 찾는다
- 가설을 세우고 실험으로 검증한다 (추측으로 코드를 수정하지 않는다)
- Defense in depth — 같은 유형의 버그가 재발하지 않도록 방어 계층을 추가한다
Resources
| Priority | Type | Resource | Description |
|---|---|---|---|
| HIGH | ref | root-cause-tracing | 5 Whys + 가설-실험 루프 상세 가이드 |
Quick Rules
Debugging Loop
- Reproduce — 버그를 100% 재현하는 최소 조건 확보
- Hypothesize — 원인 가설을 1~3개 세우고 가능성 순으로 정렬
- Test — 각 가설을 실험으로 검증 (로그 추가, breakpoint, 입력 변경)
- Fix — 근본 원인 수정 (증상 대응 X)
- Verify — 원래 재현 조건에서 버그 사라짐 확인
- Prevent — 회귀 테스트 추가, 방어 로직 보강
Root Cause Categories
| 카테고리 | 예시 |
|---|---|
| State | 예기치 않은 상태 변이, race condition |
| Data | 잘못된 입력, null/undefined, 타입 불일치 |
| Logic | 잘못된 조건, off-by-one, 순서 오류 |
| Environment | 설정 차이, 의존성 버전, OS 차이 |
| Integration | API 응답 변경, 타이밍, 네트워크 |
Anti-Patterns
- Shotgun debugging: 여러 곳을 동시에 수정 → 원인 특정 불가
- Print-and-pray: console.log만 추가하고 가설 없이 실행 반복
- Blame game: "내 코드 문제 아닌데" → 증거 없이 외부 원인 지목
Checklist
| Priority | Item |
|---|---|
| CRITICAL | 재현 조건이 명확한가 |
| CRITICAL | 가설을 세운 후 수정했는가 (추측 수정 X) |
| HIGH | 근본 원인을 찾았는가 (증상 대응만 하지 않았는가) |
| HIGH | 회귀 테스트를 추가했는가 |
| MEDIUM | 같은 유형의 버그를 방지하는 방어 로직이 있는가 |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 61 lines · 67 tokens per session scan A c8bf9acbb41c
tsq-debugging is a skill published in the GitHub repository sonature-lab/timsquad (11 stars, last pushed 7d ago), licensed MIT. It adds 67 tokens to every session and 663 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 2026-08-30.
Other skills, from other repositories
mass-line
触发：当你需要收集多方意见、把零散反馈整合成可执行方案，或把方案带回真实使用者/执行者验证时调用；常见信号包括 stakeholder input、user feedback、意见汇总、对齐与验证。 English: Trigger when input must be gathered from many people, synthesized into a clearer plan, and returned to the affected users or executors for validation. Use this skill for a collect-synthesize-validate loop.
workflows
触发：当你面临的任务明显需要多个思想武器协作时调用；常见信号包括：从零启动新项目、攻坚复杂疑难问题、对已有方案进行迭代优化。此 skill 提供标准化的跨 skill 工作流组合，解决"应该先用哪个 skill、怎么衔接"的问题。 English: Trigger when a task clearly requires multiple skills in sequence. Use this skill to select a standard workflow that chains skills together, defines data handoff between steps, and specifies…
protracted-strategy
触发：当目标长期、任务复杂、资源暂时处于劣势，或短期无法速胜但又不能放弃时调用；常见信号包括 long-term effort、phased plan、endurance、战略耐心、需要分阶段推进。 English: Trigger when the work is long-horizon, difficult, and unlikely to be won quickly. Use this skill to divide the effort into stages, keep strategic confidence, and accumulate small wins into overall victory.
practice-cognition
触发：当你提出了方案、假设或判断，需要通过实践验证、试错迭代或复盘升级认知时调用；常见信号包括 experiment、prototype、validate、iterate、feedback loop。 English: Trigger when an idea, hypothesis, or plan must be tested in practice and improved through iteration. Use this skill to move from action to understanding and back to action in a spiral learning loop.
contradiction-analysis
触发：当问题复杂、存在多个冲突因素、优先级不清，或你不知道应该先解决什么时调用；常见信号包括 trade-off、瓶颈、根因不明、主次不清、多个问题互相牵制。 English: Trigger when a problem contains competing forces, unclear priorities, or no obvious entry point. Use this skill to identify contradictions, isolate the principal contradiction, classify its nature, and choose the right response.
systematic-debugging
4-phase root cause debugging: understand bugs before fixing.