uberrca

Build evidence-backed RCA ladders identifying missing invariants for recurring failures.

Updated Apr 30, 2026
One-click install
npx skills add https://github.com/rdleclerc/agentic-uber-skills --skill uberrca
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: uberrca
Source: https://github.com/rdleclerc/agentic-uber-skills/tree/main/uberrca
Command: npx skills add https://github.com/rdleclerc/agentic-uber-skills --skill uberrca

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

UberRCA prevents repeated failures by forcing evidence-backed, class-level root cause analysis before proposing durable patches.

Core Features & Use Cases

  • RCA ladder to class-level cause: Moves from symptom and immediate failure to enabling conditions, failed invariants, upstream admission failures, recovery/detection gaps, and class-level design causes.
  • Proximate-cause rejection: Treats “prompt told the agent,” “the model erred,” and “it timed out” as incomplete until deeper missing policies, state constraints, or monitors are identified.
  • Self-challenge and convergence tests: Requires the analyst to prove the cause names an enforceable invariant whose enforcement would make the failure class impossible.
  • Repeated-failure workflow: If the same failure family repeats (notably at five consecutive clear test failures), it preserves evidence, halts blind patching, and routes revised hypotheses to planning/routing skills.

Quick Start

Use uberrca to investigate why a recurring bug or agentic-system incident keeps happening and to identify the upstream invariant whose enforcement would have prevented the failure class.

Frequently Asked Questions about uberrca

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find the root cause of recurring test failure loops instead of just patching symptoms?

Root cause analysis of recurring test failure loops requires building an evidence-backed RCA ladder that rejects proximate causes like model errors and identifies the missing invariant allowing the failure class to repeat. UberRCA enforces this depth-floor check before any patch is proposed.

Why does my agentic workflow keep timing out and leaving inconsistent state?

Agentic workflow timeouts leaving inconsistent work indicate a missing state constraint or recovery gap. Root cause analysis maps these enabling conditions to class-level design causes, enforcing an upstream invariant that prevents the failure rather than just retrying the operation.

What is the best way to perform incident response for repeated bugs in system design?

Incident response for repeated bugs benefits from a structured RCA ladder moving from symptom to class-level design cause. This approach distinguishes proximate, enabling, and class-level causes, then maps durable fixes to the lowest enforceable layer to make the failure class impossible.

How do I prove a proposed fix actually prevents an incident from happening again?

To prove a fix prevents recurrence, root cause analysis applies a self-challenge convergence test requiring the analyst to name an enforceable invariant whose enforcement would make the failure class impossible. A proposed patch is rejected as incomplete if it only addresses a proximate cause.

When should I stop blind patching during repeated agentic-system failures?

Blind patching should be halted when a failure family repeats, notably after five consecutive clear test failures. Root cause analysis then preserves evidence, stops further patching, and routes revised hypotheses to planning or routing skills to identify the missing policy or state constraint.

Can root cause analysis identify missing invariants in suspicious edge cases?

Yes, root cause analysis applies to suspicious edge cases where a proposed patch may be only proximate. It investigates the upstream admission failure and failed invariants, mapping the durable fix to the lowest enforceable layer to eliminate the entire failure class.