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 skills/nguyenthienthanh/aura-frog/deep-debuggingnpx skills add nguyenthienthanh/aura-frog --skill deep-debugginggit clone --depth 1 https://github.com/nguyenthienthanh/aura-frogWrote 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/nguyenthienthanh/aura-frog/deep-debugging)<a href="https://agentmods.dev/skills/nguyenthienthanh/aura-frog/deep-debugging"><img src="https://agentmods.dev/badge/skills/nguyenthienthanh/aura-frog/deep-debugging.svg" alt="Measured on agentmods" 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 | $0.00049 | $0.01459 |
| Opus 5 | $0.00024 | $0.00730 |
| Sonnet 5 | $0.00010 | $0.00292 |
| Haiku 4.5 | $0.00005 | $0.00146 |
Grade A, and why
deep-debugging 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 3d 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI-consumed reference. Optimized for Claude to read during execution. Human-readable explanation: see docs/architecture/HIERARCHICAL_PLANNING.md or docs/getting-started/ depending on topic.
Deep Debugging
For bugs where bugfix-quick fails. Apply scientific method, not vibes.
Escalation path: bugfix-quick (< 15 min, clear cause) → deep-debugging (scientific method)
Uses: tree-of-thoughts skill for hypothesis trees, chain-of-verification for claim validation
When to Use vs. bugfix-quick
| Signal | Use |
|---|---|
| Stack trace points to clear line | bugfix-quick |
| Reproduces 100% of the time | bugfix-quick |
| Happens in known edge case | bugfix-quick |
| Intermittent / flaky | deep-debugging |
| Multiple plausible causes | deep-debugging |
| "Works on my machine" class | deep-debugging |
| Timing / race conditions | deep-debugging |
| Production-only, can't repro locally | deep-debugging |
The Protocol
Step 1 — Reproduce reliably
Cannot debug what you can't reproduce. Goals:
- Minimum reproduction case (strip all non-essential code)
- Document trigger conditions (env, timing, order of operations)
- If intermittent: repeat N times, calculate failure rate
If can't reproduce: STOP. You can't debug. Alternative: add observability (logging, metrics, traces) to production to catch the next occurrence. Don't guess.
Step 2 — Form a hypothesis tree (via tree-of-thoughts)
Don't jump to the first suspicion. Enumerate possibilities:
Root: Login fails intermittently in production
├── Branch A: Session store issue
│ ├── A1: Redis connection pool exhausted
│ ├── A2: Cookie domain mismatch
│ └── A3: Session expiry race condition
├── Branch B: Load balancer / infra
│ ├── B1: Sticky session misconfigured
│ └── B2: TLS termination timing
└── Branch C: Auth service
├── C1: JWT clock drift
└── C2: Rate limit hit
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.
- 3d ago First seen · 164 lines · 49 tokens per session scan A 54e578d3a150
deep-debugging is a skill published in the GitHub repository nguyenthienthanh/aura-frog (24 stars, last pushed 9d ago), licensed MIT. It adds 49 tokens to every session and 1,459 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 2026-08-30.
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