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 Miaoge-Ge/coding-agent-skills --skill debugging-expertgit clone --depth 1 https://github.com/Miaoge-Ge/coding-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/miaoge-ge/coding-agent-skills/debugging-expert)<a href="https://agentmods.dev/skills/miaoge-ge/coding-agent-skills/debugging-expert"><img src="https://agentmods.dev/badge/skills/miaoge-ge/coding-agent-skills/debugging-expert/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/miaoge-ge/coding-agent-skills/debugging-expert"><img src="https://agentmods.dev/badge/skills/miaoge-ge/coding-agent-skills/debugging-expert.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 | $0.00074 | $0.00961 |
| Opus 5.5 | $0.00030 | $0.00384 |
| Sonnet 5.5 | $0.00015 | $0.00192 |
| Haiku 4.5 | $0.00007 | $0.00096 |
Grade A, and why
debugging-expert 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debugging Expert
Reproduce, then bisect. The bug is rarely where you think — follow evidence, change one variable at a time, and fix the cause (with a regression test), not the symptom.
When to Use
- A bug, crash, exception, or wrong output to diagnose.
- Intermittent / "works on my machine" / heisenbug situations.
- Locating which change introduced a regression.
- Stuck guessing and editing code at random.
When NOT to Use
- Writing the regression test after diagnosis →
testing-expert. - It's slow, not wrong →
performance-expert. - Refactoring without a defect →
refactoring-expert.
The Method
1. Reproduce reliably first
- Get a minimal, deterministic reproduction before changing anything — you can't confirm a fix for a bug you can't trigger. Pin inputs, environment, versions, and timing.
- For intermittent bugs, find what increases the rate (load, ordering, specific data, concurrency) and amplify it; add logging to capture the failing case.
2. Read the evidence
- Read the entire error and stack trace top to bottom — the root cause is often above the most obvious frame. Don't skim or assume.
- Check what changed:
git log/git diffsince it last worked, recent deploys, dependency bumps, config/env differences. Inspect logs around the failure timestamp.
3. Hypothesize → predict → test
- Form one hypothesis, predict exactly what you'd observe if it's true, then test that prediction. Confirm or eliminate before moving on.
- Bisect the search space: binary-search the code path, the input data, or history (
git bisect). Add assertions/logging at the boundary between "still correct" and "already wrong" to bracket the defect. - Question assumptions, including "this library/my framework can't be the problem." Verify, don't believe.
4. Fix the cause, prevent recurrence
- Explain why it happened before patching. Fix the root cause, not the visible symptom. Add a test that fails without the fix, then look for sibling bugs of the same class.
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 · 78 lines · 74 tokens per session scan A 5962894d27cd
debugging-expert is a skill published in the GitHub repository Miaoge-Ge/coding-agent-skills (7 stars, last pushed 4mo ago), licensed MIT. It adds 74 tokens to every session and 961 once invoked, about $0.0003 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 2026-08-31.
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