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acm-bug-hunter

Hunt bugs in ACM feature implementations using a 10-dimension investigation.

3|4|Updated Jul 25, 2025
Search Tags:#investigation#feature implementation#bug hunting#ACM#adversarial architecture
One-click install
npx skills add https://github.com/stolostron/acm-ai-qe --skill acm-bug-hunter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: acm-bug-hunter
Source: https://github.com/stolostron/acm-ai-qe/tree/main/.claude/skills/acm-bug-hunter
Command: npx skills add https://github.com/stolostron/acm-ai-qe --skill acm-bug-hunter

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires acm-source, jira, neo4j-rhacm, polarion, acm-search, acm-kubectl, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Identifies bugs in ACM feature implementations that might be missed by test cases, through a systematic 10-dimension investigation process.

Core Features & Use Cases

  • Systematic Analysis: Uses a 10-dimension model to investigate ACM feature implementations.
  • Adversarial Architecture: Spawns focused subagents for each dimension to prevent self-bias.
  • Confidence-Aware Feedback Loops: Incorporates confidence-aware feedback for honesty and thoroughness.
  • Cross-Component Probing: Performs integration probing across component boundaries.

Quick Start

Run the 'acm-bug-hunter' skill with a Polarion test case ID or a local .md file.

Frequently Asked Questions about acm-bug-hunter

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

FAQPage Schema
How do I investigate ACM feature implementations for bugs missed by test cases?▼

Yes, you can hunt for bugs in ACM features without a live cluster. The investigation process works with or without a live cluster by analyzing test cases from Polarion or local .md files and probing across component boundaries using source code and dependency graphs.

Do I need JIRA and Polarion access to perform systematic bug hunting in ACM?▼

Adversarial architecture improves bug hunting by spawning focused subagents for each investigation dimension. This structure prevents self-bias and ensures thoroughness by using confidence-aware feedback loops to challenge findings across component boundaries.

What's the best way to start an ACM bug investigation using test cases?▼

The best way to start an ACM bug investigation is to provide a Polarion test case ID or a local .md file. The system uses this input to initiate a cross-component probing process across ten analysis dimensions to find hidden implementation defects.

Are there limitations when using automated analysis for ACM feature bugs?▼

A limitation of automated ACM bug analysis is its dependency on external integrations; the process requires simultaneous access to JIRA, Polarion, ACM Source, and Neo4j MCPs to function. It also relies heavily on the initial quality of the provided test cases.

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