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 skills add codebygarv/Ai-skills --skill root-cause-diagnosergit clone --depth 1 https://github.com/codebygarv/Ai-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/skills/codebygarv/ai-skills/root-cause-diagnoser)<a href="https://agentmods.dev/skills/codebygarv/ai-skills/root-cause-diagnoser"><img src="https://agentmods.dev/badge/skills/codebygarv/ai-skills/root-cause-diagnoser.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 | $0.00036 | $0.00309 |
| Opus 5 | $0.00018 | $0.00154 |
| Sonnet 5 | $0.00007 | $0.00062 |
| Haiku 4.5 | $0.00004 | $0.00031 |
Grade A, and why
root-cause-diagnoser 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
Purpose
Drill past surface-level symptoms and immediate triggers to uncover the systemic, architectural, and organizational root causes of engineering failures.
When to Use
- Post-incident reviews and postmortems.
- Recurring bugs that keep resurfacing after quick patches.
- Flaky systems where the immediate fix failed to prevent secondary fallout.
What to Analyze
- Immediate Trigger: What directly caused the error?
- Propagation Chain: How did the failure cascade through the system?
- Detection Delay: Why was the issue not caught in CI, staging, or monitoring?
- 5-Whys Iteration: Drill 5 levels deep into process, architecture, and code.
- Systemic Defenses: What automated safeguards or architectural barriers are missing?
Output Format
- Incident Summary: Exact failure statement.
- 5-Whys Diagnostic Chain: Clear causal progression from trigger to root cause.
- Contributing Factors: Process, tooling, architecture, and observability factors.
- Corrective Actions (Actionable): Specific engineering tickets categorized into Immediate, Medium-term, and Prevention.
Avoid
- Stopping at human error ("Developer made a typo").
- Proposing generic solutions like "Be more careful in code review".
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 35 lines · 36 tokens per session scan A 033984722a5b
root-cause-diagnoser is a skill published in the GitHub repository codebygarv/Ai-skills (25 stars, last pushed 19d ago), licensed MIT. It adds 36 tokens to every session and 309 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 2026-09-03.
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