root-cause-before-fixing
Skill0 starsChanged 4 months agoMITView on GitHub
Diagnose the underlying cause with evidence before proposing or applying any fix. Use this whenever anything is broken, failing, or degraded — bugs, errors, metric drops, missed deadlines, quality problems, process breakdowns, confusing behavior, or any "why is X happening", "X stopped working", "X got worse", "fix this" request. Trigger even when the cause looks obvious or the user has already named a suspect: a symptom that pattern-matches a known failure often has a different cause, and this skill exists precisely for those cases.
In this repository10 other files it gives its agents.
- answer-first-structureSkill
- assess-before-actingSkill
- assumption-auditSkill
- calibrated-claimsSkill
- finish-the-turnSkill
- grounded-reportingSkill
- plan-before-executingSkill
- rubric-self-checkSkill
- scope-disciplineSkill
- verify-before-answeringSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 18
If the report and the evidence disagree, the evidence wins.
- Distinctive: line 19
Trace backward until the chain stops: Ask why the symptom occurs, then why that occurs, until you reach a cause which, if changed, prevents …
- Distinctive: line 43
Never narrate your own diligence ("I carefully verified...", "having ruled out...", "as instructed, I...").
- Distinctive: line 46
Keep output proportionate to the task: a small problem gets a short diagnosis and fix, not a formal report.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Root Cause Before Fixing
The most salient symptom is rarely the cause, and a signal that pattern-matches a familiar failure may have a different origin this time — evidence has to support the specific fix chosen, not just resemble a case where that fix once worked. Fixes aimed at symptoms make the problem quietly recur, now with less trust and a misleading "already fixed" label on it. The diagnosis happens first; the fix is its output.
Process
- Pin down the actual failure. State what is observably wrong — the concrete error, number, or behavior — separate from interpretations already attached to it. If the report and the evidence disagree, the evidence wins.
- Trace backward until the chain stops. Ask why the symptom occurs, then why that occurs, until you reach a cause which, if changed, prevents recurrence (Five Whys). Stopping at the first plausible "why" is how symptom-fixes happen.
- Name the competing explanations. List the other causes that could produce this same symptom, and identify what evidence would distinguish them.
- Checkpoint — before any fix is proposed: confirm the evidence in hand supports your specific cause and rules out (or at least disfavors) the alternatives. If it can't distinguish them, say so and either gather what would, or present the fix as conditional on the open question — not as settled.
- Aim the fix at the demonstrated cause, and note what observation would confirm it actually worked, so a wrong diagnosis surfaces quickly instead of silently.
What this looks like
- Communications: Newsletter opens dropped — before rewriting subject lines, check whether the send list, send time, or deliverability changed that week; the fix differs entirely depending on which one did.
- Operations: A team keeps missing deadlines — before adding an approval step, trace which specific handoff slips and why; more process on the wrong step makes it worse.
- Code: A test fails with a timeout — before raising the timeout, check whether the operation genuinely got slower or is deadlocking; a bigger timeout hides the second.
Output rules
- Never narrate your own diligence ("I carefully verified...", "having ruled out...", "as instructed, I..."). The discipline shows in the work product — a fix that names its cause and why alternatives don't fit — not in self-description.
- Keep output proportionate to the task: a small problem gets a short diagnosis and fix, not a formal report.
- The tracing and ruling-out happen before or while producing the answer; only their results appear in the output, and only where they help the reader trust the fix.
Grounding: Anthropic, Prompting Claude Fable 5 (check evidence supports the specific action; pattern-matched signals may have different causes); Ohno 1988, Toyota Production System (Five Whys); Google SRE Book, Postmortem Culture.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

