21-understand-research-150

Map core and boundary scopes while logging evidence-based research findings.

Updated Jan 30, 2025
One-click install
npx skills add https://github.com/MykhailoDmytriakha/my-preacher-helper --skill 21-understand-research-150
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: 21-understand-research-150
Source: https://github.com/MykhailoDmytriakha/my-preacher-helper/tree/main/.codex/skills/21-understand-research-150
Command: npx skills add https://github.com/MykhailoDmytriakha/my-preacher-helper --skill 21-understand-research-150

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a rigorous, repeatable framework for conducting deep, evidence-based research, ensuring every finding is traceable through a structured session log.

Core Features & Use Cases

  • Investigation protocol mandates a step-by-step approach including surface observation, cross-reference validation, contradiction hunting, and a structural logic proof to establish causal relationships.

  • Levels and scope tracking ensures core (100%) and boundary (50%) coverage, enabling thorough exploration of related areas without scope creep.

  • Documentation discipline requires recording findings, hypotheses, and next branches in a session log to support transparency and reproducibility across projects.

    Use cases: researchers mapping unknown domains, engineers verifying root causes, analysts building evidence trails for decisions.

Quick Start

Open a new session and start the Understand-Research 150 Protocol by recording an initial hypothesis and the core and boundary scopes in the session log.

Frequently Asked Questions about 21-understand-research-150

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

FAQPage Schema
How do I conduct structured investigation and root cause analysis with traceable evidence?

Structured investigation applies a step-by-step protocol including surface observation, cross-reference validation, and contradiction hunting to establish causal relationships. This approach captures insights with explicit evidence sources to maintain traceability and support repeatable decision-making.

What is the best way to maintain a research session log for unknown domain mapping?

A research session log dynamically records findings, hypotheses, and next branches during unknown domain mapping. This documentation discipline ensures transparency and reproducibility by tracking core and boundary scopes while capturing all insights with explicit evidence sources.

How do I prevent scope creep when exploring related areas during evidence-based research?

Prevent scope creep by mapping core scope at 100% coverage and boundary scope at 50% coverage. This levels and scope tracking method ensures thorough exploration of related areas without losing focus on the primary investigation target.

When do I need a structural logic proof in my root cause analysis workflow?

A structural logic proof is needed to establish causal relationships across interface, domain, patterns, and usage during root cause analysis. It serves as the final validation step after surface observation, cross-reference validation, and contradiction hunting.

Can I use this investigation protocol to build an evidence trail for decision-making?

Yes, this investigation protocol builds evidence trails for decisions by applying surface observation, cross-reference validation, and structural logic proofs. It captures all insights with explicit evidence sources and maintains a dynamic log to support traceability and repeatable decision-making.

Does this research workflow require any specific dependencies or environment setup to start?

No dependencies are required to start this research workflow. You simply open a new session and begin the protocol by recording an initial hypothesis alongside the core and boundary scopes directly in the session log.