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 skills add klh/speedy-claude --skill klh-systematic-debugginggit clone --depth 1 https://github.com/klh/speedy-claudeWrote 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/klh/speedy-claude/klh-systematic-debugging)<a href="https://agentmods.dev/skills/klh/speedy-claude/klh-systematic-debugging"><img src="https://agentmods.dev/badge/skills/klh/speedy-claude/klh-systematic-debugging/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.
<a href="https://agentmods.dev/skills/klh/speedy-claude/klh-systematic-debugging"><img src="https://agentmods.dev/badge/skills/klh/speedy-claude/klh-systematic-debugging.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00042 | $0.01336 |
| Opus 5 | $0.00021 | $0.00668 |
| Sonnet 5 | $0.00008 | $0.00267 |
| Haiku 4.5 | $0.00004 | $0.00134 |
Grade A, and why
klh-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 8d 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.
This is a copy
89% identical to systematic-debugging — 30 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Debugging
Part of klh/skills — personal agent skills by Klaus L. Hougesen. Install:
npx skills add klh/skills --skill klh-systematic-debugging
Overview
Four-phase debugging methodology with root cause analysis. Emphasizes NO FIXES WITHOUT ROOT CAUSE FIRST.
When to Use
- When investigating bugs or troubleshooting unexpected behavior
- When fixing test failures
Core Principle
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST.
Never apply symptom-focused patches that mask underlying problems. Understand WHY something fails before attempting to fix it.
The Four-Phase Framework
Phase 1: Root Cause Investigation
Before touching any code:
- Read error messages thoroughly - Every word matters
- Reproduce the issue consistently - If you can't reproduce it, you can't verify a fix
- Examine recent changes - What changed before this started failing?
- Gather diagnostic evidence - Logs, stack traces, state dumps
- Trace data flow - Follow the call chain to find where bad values originate
Root Cause Tracing Technique:
1. Observe the symptom - Where does the error manifest?
2. Find immediate cause - Which code directly produces the error?
3. Ask "What called this?" - Map the call chain upward
4. Keep tracing up - Follow invalid data backward through the stack
5. Find original trigger - Where did the problem actually start?
Key principle: Never fix problems solely where errors appear—always trace to the original trigger.
Phase 2: Pattern Analysis
- Locate working examples - Find similar code that works correctly
- Compare implementations completely - Don't just skim
- Identify differences - What's different between working and broken?
- Understand dependencies - What does this code depend on?
Phase 3: Hypothesis and Testing
Apply the scientific method:
- Formulate ONE clear hypothesis - "The error occurs because X"
- Design minimal test - Change ONE variable at a time
- Predict the outcome - What should happen if hypothesis is correct?
- Run the test - Execute and observe
- Verify results - Did it behave as predicted?
- Iterate or proceed - Refine hypothesis if wrong, implement if right
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.
- 8d ago First seen · 177 lines · 42 tokens per session scan A 3043f11482c9
klh-systematic-debugging is a skill published in the GitHub repository klh/speedy-claude (11 stars, last pushed 2d ago), licensed MIT. It adds 42 tokens to every session and 1,336 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to systematic-debugging, differing in 30 lines, and is treated as a copy.
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