用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/a5c-ai/babysitter --skill issue-tree-generator命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
Reference for querying the Atlas knowledge graph through its MCP tools — the SECONDARY enrichment/comparison layer that adds best-practice context to systems you have ALREADY scanned from your real sources (`az`, repos, dirs). Use when you need to look up nodes, edges, kinds, clusters, stats, or wiki pages in Atlas to compare against your real inventory. (atlas graph, query atlas, atlas mcp, search the graph, graph neighbors, atlas record, atlas kinds, enrichment layer)
Atlas turns your STATED NEED into a real systems atlas by SCANNING your actual sources (Azure via `az`, git repos, local dirs) and process/data mining them, THEN enriching against the Atlas knowledge graph. Use this skill when asked to inventory/map your real systems, scan your cloud + repos + directories, mine the real processes or data they contain, or collect their real constraints/gotchas. (atlas, scan my systems, inventory our azure account, map my repos, real systems atlas, process mining, data mining, collect nuances, system discovery)
This skill should be used when the user asks to "find skills in the wild", "assimilate popular workflows", "discover SKILL.md files in repos", "research external skills", "find workflow patterns", "survey the skill landscape", "what skills exist out there", or wants to investigate public repositories for extractable processes, babysitter plugins, and reusable procedural insights. Searches GitHub for SKILL.md files, classifies repos by archetype, and maintains structured research under docs/reference-repos/.
正在显示 SKILL.md
基于 SOC 职业分类
| name | issue-tree-generator |
| description | Generate and validate issue trees for structured problem solving with MECE validation |
| allowed-tools | ["Read","Write","Glob","Grep","Bash"] |
| metadata | {"specialization":"business-analysis","domain":"business","id":"SK-011","category":"Problem Solving"} |
| graph | {"domains":["domain:business-intelligence"],"specializations":["specialization:strategic-consulting"],"skillAreas":["skill-area:strategic-analysis","skill-area:business-analysis","skill-area:problem-solving"],"workflows":["workflow:market-analysis"],"roles":["role:strategic-planner","role:business-analyst"]} |
The Issue Tree Generator skill provides specialized capabilities for creating and validating issue trees used in structured problem solving. This skill enables hypothesis-driven analysis through proper decomposition of complex problems, MECE validation, hypothesis tracking, and synthesis of findings.
Create an issue tree for this problem:
[Problem statement]
Decompose to at least 3 levels with MECE validation.
Validate the MECE structure of this issue tree:
[Issue tree structure]
Identify overlaps and gaps.
Generate hypotheses from this issue tree:
[Issue tree structure]
Create testable hypotheses with data requirements.
Synthesize findings from these hypothesis test results:
[Hypothesis results with evidence]
Build recommendations from proved hypotheses.
This skill integrates with the following business analysis processes:
Problem Statement
├── Issue 1
│ ├── Sub-issue 1.1
│ │ ├── Sub-sub-issue 1.1.1
│ │ └── Sub-sub-issue 1.1.2
│ └── Sub-issue 1.2
├── Issue 2
│ ├── Sub-issue 2.1
│ └── Sub-issue 2.2
└── Issue 3
├── Sub-issue 3.1
└── Sub-issue 3.2
How to grow revenue?
├── Increase volume
│ ├── Acquire new customers
│ └── Increase purchase frequency
└── Increase price
├── Raise unit prices
└── Improve mix to premium
How to improve profitability?
├── Increase revenue
│ ├── Volume
│ └── Price
└── Decrease costs
├── Fixed costs
└── Variable costs
Should we enter market X?
├── Is the market attractive?
│ ├── Size and growth
│ └── Competitive dynamics
├── Can we win?
│ ├── Our capabilities
│ └── Competitive advantage
└── Is it worth it?
├── Financial returns
└── Strategic fit
| Status | Definition |
|---|---|
| Untested | Hypothesis identified, not yet tested |
| In Progress | Data collection/analysis underway |
| Proved | Evidence supports hypothesis |
| Disproved | Evidence refutes hypothesis |
| Inconclusive | Insufficient evidence either way |
| Rating | Description |
|---|---|
| Strong | Multiple reliable sources, quantitative data |
| Moderate | Some reliable sources, mixed data |
| Weak | Limited sources, primarily qualitative |
| Anecdotal | Single source, opinion-based |