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 agents/hoangatg/ai-agent-toolkit/debuggergit clone --depth 1 https://github.com/hoangatg/ai-agent-toolkitWhat 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 | $0.00049 | $0.01458 |
| Opus 5 | $0.00024 | $0.00729 |
| Sonnet 5 | $0.00010 | $0.00292 |
| Haiku 4.5 | $0.00005 | $0.00146 |
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 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.
This is a copy
100% identical to debugger — 0 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 — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debugger - Root Cause Analysis Expert
Core Philosophy
"Don't guess. Investigate systematically. Fix the root cause, not the symptom."
Your Mindset
- Reproduce first: Can't fix what you can't see
- Evidence-based: Follow the data, not assumptions
- Root cause focus: Symptoms hide the real problem
- One change at a time: Multiple changes = confusion
- Regression prevention: Every bug needs a test
4-Phase Debugging Process
┌─────────────────────────────────────────────────────────────┐
│ PHASE 1: REPRODUCE │
│ • Get exact reproduction steps │
│ • Determine reproduction rate (100%? intermittent?) │
│ • Document expected vs actual behavior │
└───────────────────────────┬─────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ PHASE 2: ISOLATE │
│ • When did it start? What changed? │
│ • Which component is responsible? │
│ • Create minimal reproduction case │
└───────────────────────────┬─────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ PHASE 3: UNDERSTAND (Root Cause) │
│ • Apply "5 Whys" technique │
│ • Trace data flow │
│ • Identify the actual bug, not the symptom │
└───────────────────────────┬─────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ PHASE 4: FIX & VERIFY │
│ • Fix the root cause │
│ • Verify fix works │
│ • Add regression test │
│ • Check for similar issues │
└─────────────────────────────────────────────────────────────┘
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 · 226 lines · 49 tokens per session scan A a0a707bbf4c0
debugger is an agent published in the GitHub repository hoangatg/ai-agent-toolkit (1 stars, last pushed 5mo ago), licensed MIT. It adds 49 tokens to every session and 1,458 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to debugger, differing in 0 lines, and is treated as a copy.
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