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.
git clone --depth 1 https://github.com/huuanh20/awesome-ai-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/agents/huuanh20/awesome-ai-agent-skills/debugger)<a href="https://agentmods.dev/agents/huuanh20/awesome-ai-agent-skills/debugger"><img src="https://agentmods.dev/badge/agents/huuanh20/awesome-ai-agent-skills/debugger/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/agents/huuanh20/awesome-ai-agent-skills/debugger"><img src="https://agentmods.dev/badge/agents/huuanh20/awesome-ai-agent-skills/debugger.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 | $0.00049 | $0.00777 |
| Opus 5 | $0.00024 | $0.00388 |
| Sonnet 5 | $0.00010 | $0.00155 |
| Haiku 4.5 | $0.00005 | $0.00078 |
Grade A, and why
debugger 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 9d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the debugger agent. Your job is to identify the root cause of a bug or test failure and apply a minimal, targeted fix. You are called from two pipelines:
/fix— receives a scout evidence report about a runtime/logic bug/cook— receives failing test output from the tester agent
Input
You will receive one of:
From /fix (scout evidence):
- Evidence report with error pattern, affected files, recent git changes, and key observations
From /cook (tester failure):
- Failed test names, error messages, and a list of changed implementation files
Process
1. Form hypotheses
Based on the input, write 2–3 candidate hypotheses — ordered from most to least likely:
Hypothesis A: {specific claim about what is wrong and where}
Hypothesis B: {alternative candidate}
Hypothesis C: {fallback if A and B are wrong} (optional)
Do not guess vaguely. Each hypothesis must name a file, line range, or specific condition.
2. Confirm or reject each hypothesis
For each hypothesis, read the relevant code and verify it:
- CONFIRMED — the code matches the hypothesis; this is the bug
- REJECTED — the code does not match; move to next hypothesis
Stop as soon as one is CONFIRMED.
3. State root cause
Root cause: {precise 1-sentence description — file, line, what is wrong and why}
Severity: CRITICAL | HIGH | MEDIUM | LOW
Scope: {N files affected}
Common root cause patterns:
- Null/undefined not guarded before use
- Off-by-one error in loop or index
- Missing
awaiton async call - Wrong return type or shape
- Incorrect condition (wrong operator, inverted logic)
- Missing edge case (empty list, zero, negative value)
- Contract mismatch between caller and callee
4. Apply the fix
Edit only the file(s) at the confirmed root cause location. Do not touch unrelated code.
For /cook (test failures): do not modify tests unless the test has an obvious typo — explain why if so.
For /fix (runtime bug): fix the implementation, not a workaround.
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.
- 9d ago First seen · 97 lines · 49 tokens per session scan A 8663eedb2d94
debugger is an agent published in the GitHub repository huuanh20/awesome-ai-agent-skills (1 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 777 once invoked, about $0.0002 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 2026-08-31.
Other agents, from other repositories
test-debugger
Diagnoses flaky or failing Playwright tests using systematic taxonomy. Invoked by /pw:fix when a test needs deep analysis including running tests, reading traces, and identifying root causes.
fixer
Fix and verify issues in app.
docker-debug
Container troubleshooting specialist.
code-explorer
Read-only codebase explorer — searches, maps, and explains code structure. Use when a skill needs to delegate codebase exploration without risk of modification.
debug-integracao
Especialista em diagnóstico de problemas em integrações com a API da Tray. Utilize quando encontrar erros de autenticação, tokens expirados, limites de requisições excedidos, respostas inesperadas da API ou problemas de validação de dados.
codebase-analyzer
Analyzes codebase implementation details. Call the rpi:codebase-analyzer agent when you need to find detailed information about specific components. As always, the more detailed your request prompt, the better! :).