sherlock

Identify root causes by collecting facts, ranking hypotheses, and guiding evidence-based elimination.

4|Updated Apr 30, 2026
One-click install
npx skills add https://github.com/satsilem/claude-skills-pantheon --skill sherlock-satsilem
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sherlock
Source: https://github.com/satsilem/claude-skills-pantheon/tree/main/skills/sherlock
Command: npx skills add https://github.com/satsilem/claude-skills-pantheon --skill sherlock-satsilem

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Sherlock helps teams identify the true root causes of problems by collecting facts, formulating hypotheses, and guiding evidence-based elimination to avoid patching symptoms.

Core Features & Use Cases

  • Stepwise fact gathering, hypothesis generation, elimination, and confirmation to reveal the cause with an evidence chain.
  • Ideal for debugging, incident RCA, performance issues, and integration failures across software and operations.
  • Outputs a structured root-cause report with evidence chain and recommended next steps.

Quick Start

Describe the observed incident and logs to Sherlock, then request a root-cause analysis.

Frequently Asked Questions about sherlock

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

FAQPage Schema
How do I perform root-cause analysis for a software incident?▼

Root-cause analysis for a software incident requires collecting facts, generating ranked hypotheses, and guiding evidence-based elimination. You provide observed symptoms, timelines, changes, and logs to receive a structured report with the confirmed cause and evidence chain.

What is the best way to troubleshoot a failed service integration?▼

Troubleshooting a failed service integration involves systematically articulating the root cause by gathering facts and eliminating hypotheses based on evidence. This approach avoids patching symptoms and outputs a report with recommended next steps for resolution.

Can I use log analysis to debug performance issues across my systems?▼

Log analysis can debug performance issues across software systems by feeding observed data and timelines into a structured troubleshooting process. This generates ranked hypotheses to identify the true root cause rather than just addressing surface symptoms.

How do I structure incident data for effective debugging?▼

Effective debugging requires structured input including observed symptoms, timelines, recent changes, and available logs or data. Providing this structured context allows for accurate fact gathering, hypothesis generation, and evidence-based elimination.

Why does patching symptoms fail to resolve recurring incidents?▼

Patching symptoms fails because it bypasses root-cause identification, allowing the underlying issue to persist or recur. True incident resolution requires collecting facts and confirming an evidence chain to eliminate the actual cause.

When should I avoid using a systematic RCA approach for troubleshooting?▼

You should avoid systematic RCA for trivial errors with obvious causes, as the structured fact-gathering and hypothesis-ranking process adds unnecessary overhead. It is designed for complex debugging, incidents, and integration failures requiring deep investigation.