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/itallstartedwithaidea/agent-skills/systematic-debuggingnpx skills add itallstartedwithaidea/agent-skills --skill systematic-debugginggit clone --depth 1 https://github.com/itallstartedwithaidea/agent-skillsWrote 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/itallstartedwithaidea/agent-skills/systematic-debugging)<a href="https://agentmods.dev/skills/itallstartedwithaidea/agent-skills/systematic-debugging"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/systematic-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 | $0.00024 | $0.01353 |
| Opus 5 | $0.00012 | $0.00677 |
| Sonnet 5 | $0.00005 | $0.00271 |
| Haiku 4.5 | $0.00002 | $0.00135 |
Grade A, and why
systematic-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 yesterday.
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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Debugging
Part of Agent Skills™ by googleadsagent.ai™
Description
Systematic Debugging replaces trial-and-error fixes with a disciplined four-phase root cause analysis process. The agent reproduces the bug reliably, generates ranked hypotheses, tests each hypothesis with minimal instrumentation, and applies a targeted fix with defense-in-depth hardening. No fix is applied without first understanding why the bug exists.
Agents are prone to "shotgun debugging"—changing multiple things simultaneously and hoping the problem disappears. This skill enforces scientific rigor: one variable at a time, observable evidence at each step, and a clear causal chain from root cause to fix. The agent must articulate the root cause in plain language before writing any corrective code.
After the immediate fix, the agent applies defense-in-depth: adding assertions, input validation, or monitoring that would catch the same class of bug in the future. The debugging session concludes with a post-mortem note documenting the root cause, the fix, and the preventive measures added.
Use When
- A test fails unexpectedly or intermittently
- A user reports a bug with a stack trace or reproduction steps
- Code behaves differently in production than in development
- An error message is unclear or misleading
- Multiple potential causes exist and guessing would waste time
- A previous fix attempt did not resolve the issue
How It Works
graph TD
A[Bug Report] --> B[Phase 1: Reproduce]
B --> C{Reproducible?}
C -->|No| D[Gather More Context]
D --> B
C -->|Yes| E[Phase 2: Hypothesize]
E --> F[Rank Hypotheses by Likelihood]
F --> G[Phase 3: Test Top Hypothesis]
G --> H{Root Cause Found?}
H -->|No| I[Eliminate Hypothesis]
I --> F
H -->|Yes| J[Phase 4: Fix + Harden]
J --> K[Write Regression Test]
K --> L[Apply Defense-in-Depth]
L --> M[Document Post-Mortem]
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.
- yesterday First seen · 140 lines · 24 tokens per session scan A b26f5b5c4f17
systematic-debugging is a skill published in the GitHub repository itallstartedwithaidea/agent-skills (36 stars, last pushed 4mo ago), licensed MIT. It adds 24 tokens to every session and 1,353 once invoked, about $0.0001 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 2026-09-03.
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