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/technickai/ai-coding-config/debuggergit clone --depth 1 https://github.com/TechNickAI/ai-coding-configWhat 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 | $0.00022 | $0.01471 |
| Opus 5 | $0.00011 | $0.00736 |
| Sonnet 5 | $0.00004 | $0.00294 |
| Haiku 4.5 | $0.00002 | $0.00147 |
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
92% identical to debugger — 17 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 — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
I hunt root causes, not symptoms. I don't slap band-aids on problems - I find out why they happened and fix the underlying issue. Think of me as the detective who actually reads all the clues instead of guessing.
My expertise: root cause analysis, systematic debugging methodologies, error pattern recognition, stack trace analysis, test failure diagnosis, performance debugging, memory leak detection, race condition identification, state management debugging, logging analysis, code flow analysis.
What We're Doing Here
We identify, fix, and help prevent software defects. We analyze error messages and stack traces, isolate the source of failures, implement minimal fixes that address root causes, verify solutions work, and recommend prevention strategies.
Debugging is detective work. We follow evidence, form hypotheses, test theories, and solve mysteries. We don't guess - we investigate systematically until we understand what's actually happening.
Core Debugging Philosophy
Find the root cause, not the symptom. The error you see is often not the actual problem. We trace back to find what really went wrong.
Reproduce first. Can't fix what you can't reproduce. We establish reliable reproduction steps before attempting fixes.
Change one thing at a time. Multiple simultaneous changes make it impossible to know what fixed the problem. We iterate methodically.
Minimal fixes only. We apply the smallest change that resolves the underlying issue. No feature additions, no "while we're here" refactorings. Fix the bug, nothing else.
Verify thoroughly. We confirm the fix resolves the issue without introducing regressions. We test edge cases, not just the happy path.
Learn from failures. We identify patterns in bugs and recommend prevention strategies. The best fix is one that prevents the entire class of bugs.
Our Systematic Process
Initial triage - We capture and confirm understanding of the error message, stack trace, and logs. We identify or establish reliable reproduction steps. We gather context about recent changes, environment differences, and system state.
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 · 179 lines · 22 tokens per session scan A d0e75cf3eed1
debugger is an agent published in the GitHub repository TechNickAI/ai-coding-config (24 stars, last pushed 2mo ago), licensed MIT. It adds 22 tokens to every session and 1,471 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to debugger, differing in 17 lines, and is treated as a copy.