bambu-studio-ai
Bambu Lab 3D printer control and automation. Activate when user mentions: printer status, 3D printing, slice, analyze model, generate 3D, AMS filament, print monitor, Bambu Lab, or any 3D printing task. Full pi...
Technical Debt Audit
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install 1kalin/afrexai-tech-debt-audit打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Systematic technical debt assessment for engineering teams. Identifies, scores, and prioritizes debt across your codebase with business impact analysis and remediation roadmaps.
Describe your system, stack, and known pain points. The agent audits systematically:
"Audit our technical debt. We're a Node.js/React SaaS with 180K LOC,
12 engineers. Known issues: monolithic API, no integration tests,
3 deprecated dependencies, manual deployments."
Priority Score = (Risk × 3) + (Business Impact × 2) + (1/Effort × 1)
Higher score = fix first. Quick wins (low effort, high risk) surface to the top.
| Category | Examples | Typical Carrying Cost |
|---|---|---|
| Architecture | Monoliths, tight coupling, wrong patterns | 15-25% velocity drag |
| Code Quality | Duplication, god classes, no standards | 10-20% velocity drag |
| Dependencies | Outdated libs, security vulns, EOL frameworks | 5-15% + incident risk |
| Testing | No tests, flaky tests, manual QA only | 20-40% bug-fix overhead |
| Infrastructure | Manual deploys, no monitoring, snowflake servers | 10-30% ops overhead |
| Documentation | No onboarding docs, tribal knowledge | 2-4 weeks per new hire |
# Technical Debt Audit Report
## Executive Summary
- Total debt items: [N]
- Estimated carrying cost:...
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
Systematic technical debt assessment for engineering teams. Discovers, scores, and prioritizes debt across your entire stack with dollar-cost estimates and a remediation roadmap.
Most engineering teams spend 23-42% of their time on tech debt but never measure it. This skill turns vague "we should refactor" conversations into a scored, prioritized action plan with real cost numbers.
Install via ClawHub, then describe your system and known pain points. The agent handles the rest.
Built by AfrexAI | AI Revenue Calculator | Agent Setup Wizard
# Technical Debt Audit Systematic technical debt assessment for engineering teams. Identifies, scores, and prioritizes debt across your codebase with business impact analysis and remediation roadmaps. ## What It Does 1. **Debt Discovery** — Categorizes debt: architecture, code quality, dependency, testing, infrastructure, documentation 2. **Impact Scoring** — Rates each item on effort (1-5), risk (1-5), and business impact (1-5) using a weighted formula 3. **Cost Modeling** — Estimates carrying cost per sprint in developer-hours and dollars 4. **Remediation Roadmap** — Generates a prioritized paydown plan with quick wins, scheduled work, and strategic rewrites 5. **Executive Summary** — One-page board-ready report showing debt-to-velocity ratio and projected savings ## Usage Describe your system, stack, and known pain points. The agent audits systematically: ``` "Audit our technical debt. We're a Node.js/React SaaS with 180K LOC, 12 engineers. Known issues: monolithic API, no integration tests, 3 deprecated dependencies, manual deployments." ``` ## Scoring Formula **Priority Score** = (Risk × 3) + (Business Impact × 2) + (1/Effort × 1) Higher score = fix first. Quick wins (low effort, high risk) surface to the top. ## Debt Categories | Category | Examples | Typical Carrying Cost | |----------|----------|----------------------| | Architecture | Monoliths, tight coupling, wrong patterns | 15-25% velocity drag | | Code Quality | Duplication, god classes, no standards | 10-20% velocity drag | | Dependencies | Outdated libs, security vulns, EOL frameworks | 5-15% + incident risk | | Testing | No tests, flaky tests, manual QA only | 20-40% bug-fix overhead | | Infrastructure | Manual deploys, no monitoring, snowflake servers | 10-30% ops overhead | | Documentation | No onboarding docs, tribal knowledge | 2-4 weeks per new hire | ## Output Format ```markdown # Technical Debt Audit Report ## Executive Summary - Total debt items: [N] - Estimated carrying cost:...
# Technical Debt Audit Systematic technical debt assessment for engineering teams. Discovers, scores, and prioritizes debt across your entire stack with dollar-cost estimates and a remediation roadmap. Most engineering teams spend 23-42% of their time on tech debt but never measure it. This skill turns vague "we should refactor" conversations into a scored, prioritized action plan with real cost numbers. ## Features - **6-category debt taxonomy** — architecture, code quality, dependencies, testing, infrastructure, documentation - **Weighted priority scoring** — risk × 3, business impact × 2, inverse effort × 1 - **Carrying cost estimates** — dollars per month, velocity drag percentage - **Remediation roadmap** — quick wins → scheduled work → strategic rewrites - **Executive summary** — board-ready one-pager with debt-to-velocity ratio ## Who It's For - Engineering managers tracking team velocity - CTOs presenting debt reduction plans to the board - Tech leads prioritizing refactoring work - Agencies auditing client codebases before taking over ## Quick Start Install via ClawHub, then describe your system and known pain points. The agent handles the rest. --- Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) | [AI Revenue Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) | [Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/)
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