ironbee-analyze

分类: 数据与AI | 上传者: ironbee-ai | 下载: 0 | 版本: v1.0（最新）

通过验证指标、问题和修复的语义解释来运行 IronBee 会话分析

更新日志: Source: GitHub https://github.com/ironbee-ai/ironbee-cli

目录结构

当前层级: tree/main/src/clients/cursor/commands/ironbee-analyze/

📄 SKILL.md 1.8 KB

SKILL.md

---
name: ironbee-analyze
description: Run IronBee session analysis with semantic interpretation of verification metrics, issues, and fixes
disable-model-invocation: true
---

# IronBee Session Analysis

Run `ironbee analyze --json --detailed` via terminal to get raw session metrics, then provide a semantic analysis.

## Steps

1. Run `ironbee analyze --json --detailed` (all sessions) or `ironbee analyze <session-id> --json` (specific session) via terminal
2. Parse the JSON output
3. Analyze and interpret the results:

### Time Analysis
- Is the coding:verification:fix ratio healthy? (High fix% = inefficient coding)
- Is time to first verification reasonable? (Too long = agent coding without testing)

### Verification Quality
- What is the first-pass success rate? Why might it be low?
- Are enough pages and checks being tested? (Low numbers = superficial testing)

### Code Changes
- Which files are hot files? Are they expected to change frequently?
- Which files are problematic? What might be causing repeated fixes?
- Is there edit churn? (Same file in multiple fix cycles = root cause not resolved)

### Fix Effectiveness
- Are fixes working? (Low fix success rate = agent not understanding the problem)
- Is re-fail rate high? What patterns do you see in the issues?

### Semantic Analysis (LLM-powered)
- Group similar issues from verdict data into categories (e.g., "contrast issues", "event handler bugs", "API errors")
- Identify recurring patterns across sessions
- Suggest root causes for frequently failing files

### Scoring
- Interpret the efficiency, quality, and confidence scores
- Compare with project averages if cross-session data is available

## Output Format
Provide a structured report with:
- Executive summary (1-2 sentences)
- Key findings (bullet points)
- Recommendations (actionable next steps)
- Risk areas (files/patterns to watch)

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ironbee-analyze

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SKILL.md

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