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 tkellogg/open-strix --skill five-whysgit clone --depth 1 https://github.com/tkellogg/open-strixWrote 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/tkellogg/open-strix/five-whys)<a href="https://agentmods.dev/skills/tkellogg/open-strix/five-whys"><img src="https://agentmods.dev/badge/skills/tkellogg/open-strix/five-whys/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/tkellogg/open-strix/five-whys"><img src="https://agentmods.dev/badge/skills/tkellogg/open-strix/five-whys.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 155 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00096 | $0.03039 |
| Opus 5.5 | $0.00038 | $0.01216 |
| Sonnet 5.5 | $0.00019 | $0.00608 |
| Haiku 4.5 | $0.00010 | $0.00304 |
Grade A, and why
five-whys 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 1mo 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 — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Five Whys
Five Whys is a method for finding root causes. You ask "why did this happen?" and answer it honestly. Then you ask "why?" about that answer. You keep going until you hit bedrock — the structural cause that, if changed, would prevent the problem from recurring.
The goal is understanding, not blame. You're investigating a system (which includes yourself). Systems have structural properties that produce outcomes. Find the structural property, change it, and the outcome changes.
When to Use This
- Something failed or went wrong and the surface-level explanation feels incomplete
- A pattern keeps recurring despite previous fixes
- You're about to make a change and want to make sure you're fixing the right thing
- Behavior (yours or a system's) has drifted from expectations
- Someone asks "why does this keep happening?"
When NOT to Use This
- The cause is obvious and singular (typo, wrong config value, missing file)
- You're troubleshooting a known bug with a known fix
- The problem is "how do I do X?" not "why did X go wrong?"
The Process
Step 1: State the Problem
Write down what happened. Be specific. Not "it broke" but "the classifier produced 11 consecutive errors between iterations 83-93, spending 57 minutes with zero successful runs."
The problem statement is the root of your tree.
Step 2: Ask Why — And Answer It
For the problem (or any node in the tree), ask: "Why did this happen?"
Then answer it. Both the question and the answer matter equally. A question without an answer is incomplete. An answer without a clear question is unanchored.
PROBLEM: 11 consecutive classifier errors, 57 min wasted
WHY: The proposer suggested CatBoost, which isn't in the allowed algorithm list
ANSWER: The proposer has no documentation of which algorithms are available
Rules for good answers:
- An answer must be factual and verifiable. Check logs, read code, look at data. Don't speculate — investigate.
- If you can't verify an answer, say so. "I believe X but haven't confirmed" is honest. "X" stated as fact when you haven't checked is not.
- An answer should be a mechanism, not a redescription. "It failed because it was broken" is circular, not explanatory.
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.
- 1mo ago First seen · 281 lines · 96 tokens per session scan A 3c756b8e9e17
five-whys is a skill published in the GitHub repository tkellogg/open-strix (93 stars, last pushed 2mo ago), licensed MIT. It adds 96 tokens to every session and 3,039 once invoked, about $0.0004 per session on Opus 5.5. 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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