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DiologIR
DiologIROFFICIAL
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discovery-sentinel

Analyze product discovery and customer feedback to extract structured insights.

Updated Apr 10, 2026
Search Tags:#compliance#prioritization#data analysis#product discovery#customer feedback
One-click install
npx skills add https://github.com/DiologIR/diolog-plugins --skill discovery-sentinel
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: discovery-sentinel
Source: https://github.com/DiologIR/diolog-plugins/tree/main/plugins/discovery-sentinel/skills/discovery-sentinel
Command: npx skills add https://github.com/DiologIR/diolog-plugins --skill discovery-sentinel

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires persona.md, deep-research.md, discovery-2026-addendum.md, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill analyzes product discovery and customer feedback, providing structured insights and prioritized opportunities for evidence-based decision-making in regulated B2B SaaS environments.

Core Features & Use Cases

  • Signal Extraction and Classification: Identifies and classifies signals from various sources, such as interviews, feedback, and usage data.
  • Feedback Analysis and Routing: Analyzes feedback for compliance, user experience, and business impact, then routes it to the appropriate channel.
  • Prioritization and Scoring: Scores and prioritizes opportunities based on compliance, RICE, and other frameworks.
  • Output Generation: Generates detailed reports including feedback classification, discovery insights, prioritized opportunities, and action checklists.

Quick Start

Use the discovery-sentinel skill to analyze customer feedback from the attached file 'customer-feedback.md'.

Frequently Asked Questions about discovery-sentinel

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

FAQPage Schema
How do I prioritize customer feedback in compliance-heavy B2B SaaS environments?▼

Customer feedback in compliance-heavy B2B SaaS environments is prioritized using RICE and compliance frameworks to score opportunities, route feedback appropriately, and drive evidence-based decisions.

What is the best way to extract and classify product discovery signals from multiple sources?▼

Product discovery signals from interviews, feedback, and usage data are extracted and classified by analyzing the data to identify specific insights, routing feedback based on compliance and business impact.

Can I analyze customer feedback for regulated industries using persona-based frameworks?▼

Yes, analyzing customer feedback for regulated industries is supported using persona-based frameworks, deep research, and advanced analytical techniques to generate structured insights and action checklists.

How do I generate prioritized opportunity reports from raw product discovery data?▼

Prioritized opportunity reports are generated from raw product discovery data by scoring opportunities against compliance and RICE frameworks, then outputting detailed reports with feedback classification and action checklists.

Does analyzing product discovery require deep research and persona dependencies?▼

Yes, analyzing product discovery requires deep research and persona dependencies to operationalize the advanced analytical techniques needed for extracting structured insights in high-stakes environments.

What are the limitations of automated feedback analysis in high-stakes B2B SaaS?▼

Automated feedback analysis in high-stakes B2B SaaS requires specific persona and deep research dependencies to function, limiting its use in environments lacking structured operational guidance or advanced analytical setup.

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