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Systematically identifies, scores, and prioritizes technical debt across codebases with impact analysis and detailed remediation roadmaps for engineering teams.

媒体与内容

许可证:MIT-0

MIT-0 ·免费使用、修改和重新分发。无需归因。

版本:v1.0.0

统计:⭐ 0 · 531 · 0 current installs · 0 all-time installs

0

安装量(当前) 0

🛡 VirusTotal :良性 · OpenClaw :良性

Package:1kalin/afrexai-tech-debt-audit

安全扫描(ClawHub)

  • VirusTotal :良性
  • OpenClaw :良性

OpenClaw 评估

Instruction-only technical-debt auditing skill that is internally consistent with its stated purpose and requests no credentials or installs, but avoid pasting secrets when using it.

目的

Name/README/SKILL.md describe a technical-debt audit tool and the skill's requirements (none) match that purpose. There are no unexpected requested credentials, binaries, or config paths that would be disproportionate for an audit guide.

说明范围

SKILL.md is an instruction-only guide that asks the user to describe their system and pain points (expected). It does not instruct the agent to read files, access env vars, or call external endpoints. Note: the audit relies on user-supplied context, so users should avoid pasting secrets or sensitive configuration.

安装机制

No install spec and no code files — lowest risk. Nothing is downloaded or written to disk by the skill itself.

证书

The skill requires no environment variables, credentials, or config paths. There are no disproportionate secret requests relative to the skill's function.

持久

always:false and default model invocation settings. The skill does not request permanent presence or elevated system privileges.

综合结论

This skill is an instruction-only audit template and appears coherent with its purpose. Before using it: (1) confirm the source if you care about provenance (homepage/source are absent), (2) never paste API keys, private repo URLs, secrets, or full configuration files into the chat — provide high-level descriptions or sanitized examples instead, (3) test outputs on non-production data, and (4) if you want reduced risk, disable autonomous invoc…

安装(复制给龙虾 AI)

将下方整段复制到龙虾中文库对话中,由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库(龙虾 AI)执行:为本机安装 OpenClaw 技能「Technical Debt Audit」。简介:Systematically identifies, scores, and prioritizes technical debt across codeba…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装:https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/1kalin/afrexai-tech-debt-audit/SKILL.md
(来源:yingzhi8.cn 技能库)

SKILL.md

打开原始 SKILL.md(GitHub raw)

# 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: $[X]/month
- Debt-to-velocity ratio: [X]%
- Quick wins available: [N] items, [X] dev-days

## Critical (Fix This Sprint)
...

## High Priority (Next 30 Days)  
...

## Scheduled (Next Quarter)
...

## Strategic (Plan & Budget)
...

## Remediation Roadmap
Week 1-2: [Quick wins]
Month 1: [High priority]
Quarter: [Scheduled items]
```

## Why This Matters

Engineering teams spend 23-42% of development time on technical debt (Stripe Developer Report). Most don't measure it. What you don't measure, you can't manage.

---

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