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 MinhThang1009/dotclaude --skill debuggit clone --depth 1 https://github.com/MinhThang1009/dotclaudeWrote 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/minhthang1009/dotclaude/debug)<a href="https://agentmods.dev/skills/minhthang1009/dotclaude/debug"><img src="https://agentmods.dev/badge/skills/minhthang1009/dotclaude/debug/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/minhthang1009/dotclaude/debug"><img src="https://agentmods.dev/badge/skills/minhthang1009/dotclaude/debug.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 | $0.00030 | $0.01135 |
| Opus 5.5 | $0.00012 | $0.00454 |
| Sonnet 5.5 | $0.00006 | $0.00227 |
| Haiku 4.5 | $0.00003 | $0.00113 |
Grade A, and why
debug 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 1mo 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Systematic Debugging
You have been called to debug. DO NOT make random fixes until you understand the problem.
Principles
"A bug you can reproduce reliably is half-fixed."
Step 1: Gather symptoms
Ask the user (if not yet clear):
- What exactly are the symptoms? (what error, what wrong output, where does it crash)
- When does it occur? (always, randomly, only in certain environments)
- Did it work before? If so, what is the most recent change?
- Is there an error message / stack trace? Paste it in.
Step 2: Reproduce
Before guessing the cause, reproduce in the local environment:
- Run the command the user described
- Open the file, call the function, send the request — recreate the conditions that trigger the error
- Capture the full output
If CANNOT reproduce:
- Tell the user clearly
- Suggest steps to gather more information (add more logging, try different env, different version)
- DO NOT make guesses and fix blindly when reproduction has not been achieved.
Step 3: Narrow down the cause
Apply the scientific method:
- Observe: what exactly is the wrong output compared to the expected correct output?
- Hypothesize: list 2-4 plausible causes, ranked by confidence.
- Verify: for each hypothesis, identify the experiment to validate it (which file to read, which command to run, what to log). Start with the hypothesis that has the lowest verification cost.
- Narrow down: bisect — split the suspicious space in half (commit, file, function, input range) until the smallest component causing the error is found.
Tools:
git bisectfor regressions- Binary search in code: comment/uncomment to split in half
- Add logging at key points (remember to remove after fixing)
- Reproduce with the smallest possible input that triggers the error (minimal reproducer)
Step 4: Understand the cause (root cause, NOT the symptom)
When the error location is found:
- Why does this code cause the error? (specific mechanism, not just "it's wrong")
- Why was it written this way? (read git blame, read old PRs)
- Are there other places in the codebase with a similar pattern? (use Grep — fixing one place is usually not enough)
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.
- 1mo ago First seen · 114 lines · 30 tokens per session scan A 34b155d43dcd
debug is a skill published in the GitHub repository MinhThang1009/dotclaude (20 stars, last pushed 2mo ago), licensed MIT. It adds 30 tokens to every session and 1,135 once invoked, about $0.0001 per session on Opus 5.5. 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.
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