trace

Trace observed outcomes through competing hypotheses with structured evidence evaluation.

Updated May 5, 2026
One-click install
npx skills add https://github.com/HyperionBurn/searchv1beta --skill trace-hyperionburn
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: trace
Source: https://github.com/HyperionBurn/searchv1beta/tree/main/.github/skills/trace
Command: npx skills add https://github.com/HyperionBurn/searchv1beta --skill trace-hyperionburn

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps you perform evidence-driven root cause analysis when an outcome is ambiguous and you need to justify the “why” using competing explanations rather than guesswork.

Core Features & Use Cases

  • Evidence-driven causal tracing: Preserve an explicit chain from observation to hypotheses through evidence for/against.
  • Competing hypotheses in parallel: Generate and evaluate multiple distinct cause categories (implementation, environment/config/orchestration, and measurement/assumption mismatch).
  • Discriminating probe design: Recommend the single next test that would most reduce uncertainty between the top competing hypotheses.
  • Rebuttal and ranking: Use a structured rebuttal round and synthesize the best explanation with clearly stated unknowns.

Use cases: runtime regressions, performance/latency anomalies, architecture/orchestration behavior, config or routing issues, and postmortem/analysis of surprising system behavior.

Quick Start

Ask: trace this: <observation to trace> and include the exact observed result and any relevant logs or metrics you have.

Frequently Asked Questions about trace

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

FAQPage Schema
How do I perform root cause analysis for an ambiguous performance regression?

Root cause analysis for a performance regression uses evidence-driven causal tracing to generate parallel competing hypotheses, evaluate supporting evidence, and recommend a discriminating probe to validate the best explanation.

What is the best way to debug a system failure when the cause is unclear?

Debugging an unclear system failure is best handled by generating parallel competing hypotheses across implementation, configuration, and measurement categories, then using a structured rebuttal to synthesize the most probable explanation.

Can I use hypothesis testing to investigate orchestration and configuration failures?

Yes, hypothesis testing applies to orchestration and configuration failures by creating distinct causal explanations for the observed outcome and ranking them against collected evidence to identify configuration mismatches.

How do I find the next test to run when multiple root causes are possible?

Finding the next test to run requires designing a discriminating probe, which is a single targeted test recommended to most reduce uncertainty between the top competing hypotheses.

Does evidence-driven causal tracing work for analyzing surprising system behavior in a postmortem?

Evidence-driven causal tracing works for postmortem analysis by preserving an explicit chain from observation to hypotheses through evidence, ensuring the explanation of surprising system behavior is fully justified.