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 khasky/awesome-agent-skills --skill awesome-root-causegit clone --depth 1 https://github.com/khasky/awesome-agent-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/khasky/awesome-agent-skills/awesome-root-cause)<a href="https://agentmods.dev/skills/khasky/awesome-agent-skills/awesome-root-cause"><img src="https://agentmods.dev/badge/skills/khasky/awesome-agent-skills/awesome-root-cause/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/khasky/awesome-agent-skills/awesome-root-cause"><img src="https://agentmods.dev/badge/skills/khasky/awesome-agent-skills/awesome-root-cause.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00102 | $0.02134 |
| Opus 5 | $0.00051 | $0.01067 |
| Sonnet 5 | $0.00020 | $0.00427 |
| Haiku 4.5 | $0.00010 | $0.00213 |
Grade A, and why
awesome-root-cause 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.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Root Cause Analysis
Find the real cause of an incident, a recurring failure, or a process problem — the kind with no failing test to reproduce — and drive it to a durable countermeasure. Blame-free by design: the goal is a systemic fix, not a person to fault.
When to use vs awesome-bug-fix
- This skill — an outage retro, a "this keeps breaking", a data-quality or handoff or deploy-process problem, a near-miss. The failure lives in process, environment, or coordination, and you can't just run it and watch it fail.
- awesome-bug-fix — a specific code bug with a reproduction. If you can write a failing test, use that skill; come here when there's nothing to run.
If the problem is a mix (a code bug that a broken process let ship), fix the bug in awesome-bug-fix and use this skill on the process that allowed it.
Workflow
1. Frame the problem
State it as an observable gap, not a solution or a culprit: current condition vs expected condition, when it started, how often, blast radius, and how you know (the evidence — logs, tickets, timeline). If you can't state the gap concretely, gather more before analyzing.
2. Widen the candidates (fishbone)
Before drilling, sweep six cause categories so you don't fixate on the obvious one — People, Process, Technology, Environment, Methods, Materials. List candidate contributors under each. Root causes sit in Process or Methods far more often than in Technology; a purely technical cause is the exception, not the default.
3. Drill each real candidate (5-Whys)
For each surviving candidate, ask "why" down the chain. Two rules:
- Stop at a systemic gap, not a person. If a chain bottoms out at "human error", keep going: "why was that error possible?" — the true root is a missing validation, a missing automation, or an unclear procedure. A cause you can't fix by changing a person is the one worth finding.
- The count isn't magic. Stop when you reach a cause that, if removed, prevents the class of problem — whether that's three whys or seven. Don't pad to five.
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 Changed · +14 lines 379b75fa2b56
- 4d ago Changed 1ff3937d26a3
- 10d ago First seen · 92 lines · 102 tokens per session scan A 90fefe587d2d
awesome-root-cause is a skill published in the GitHub repository khasky/awesome-agent-skills (8 stars, last pushed 2d ago), licensed MIT. It adds 102 tokens to every session and 2,134 once invoked, about $0.0005 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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