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/gabriele-mastrapasqua/codex-lean-team/root-cause-debuggingnpx skills add gabriele-mastrapasqua/codex-lean-team --skill root-cause-debugginggit clone --depth 1 https://github.com/gabriele-mastrapasqua/codex-lean-teamWrote 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/gabriele-mastrapasqua/codex-lean-team/root-cause-debugging)<a href="https://agentmods.dev/skills/gabriele-mastrapasqua/codex-lean-team/root-cause-debugging"><img src="https://agentmods.dev/badge/skills/gabriele-mastrapasqua/codex-lean-team/root-cause-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 5.1 | $0.00031 | $0.00150 |
| Opus 5 | $0.00015 | $0.00075 |
| Sonnet 5 | $0.00006 | $0.00030 |
| Haiku 4.5 | $0.00003 | $0.00015 |
Grade A, and why
root-cause-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 5d 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.
What it actually says
Use an evidence-first debugging loop:
- Restate the observed failure and separate facts from assumptions.
- Identify the smallest reproducible path.
- Trace state and data across boundaries.
- Rank hypotheses by likelihood and discriminating evidence.
- Run or propose the cheapest test that eliminates the most hypotheses.
- Fix the root cause rather than masking the symptom.
- Add a regression test and verify adjacent failure modes.
Escalate to a specialist only when evidence points to that domain. Keep a short hypothesis ledger; do not dump exhaustive speculation.
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.
- 5d ago First seen · 17 lines · 31 tokens per session scan A 48bb9d3e19ae
root-cause-debugging is a skill published in the GitHub repository gabriele-mastrapasqua/codex-lean-team (3 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 150 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.
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Build or modify frontend interfaces using repository-native components while preserving accessibility, responsive behavior, state handling, and visual verification. Use for UI features, design implementation, forms, client-side defects, and frontend refactors; do not use for backend-only or infrastructure-only work.