Krishnagangwal
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CS-Fundamentals
A curated collection of Computer Science fundamentals (PDFs, notes, cheatsheets, interview question banks) for placement preparation, covering seven core subjects plus general resources.
AI 仓库情报摘要
FR-AI / ANALYSIS为什么值得关注
它强制执行严格的证据优先流程，避免过早建模；数据质量关卡可以中止或要求用户确认；自适应分析路径只生成有支持的结果。
适合谁使用
- 数据分析师和科学家
- 决策智能从业者
- 风险与合规官
- AI治理与审计团队
典型使用场景
- 需要透明证据的高风险商业或政策决策
- 模型验证与部署就绪评估
- 可复现研究（保留源数据和代码）
- 分析前的数据质量审计与准备
项目优势
- 证据优先工作流减少过拟合和无根据的推荐
- 数据就绪关卡提供明确的阻塞/确认/通过状态
- 根据案例自适应选择分析路径（描述/诊断/预测/规范）
- 可复现输出：哈希源文件、合同和机器可读结果
使用前须知
- 需要理解分析方法和证据合同才能解释输出
- 对于简单或已知问题可能过于复杂
- 依赖安装（Node.js 18+、Python 3.10+）和CLI工具，可能限制可及性
README 快速开始
High-Stakes Analytics & Decision Lab
A platform-neutral, evidence-constrained Skill for moving from an ambiguous question to a defensible analysis—and only then, when justified, to action.
What the Skill does
This Skill turns an ambiguous, consequential question into a reproducible evidence product and, only when justified, a bounded decision product. It can start from a question alone or from uploaded row-level data. Instead of assuming the data are clean, the model is useful, or a recommendation must be produced, it makes each transition conditional on visible evidence.
| Highlight | Instead of… | The Skill… |
|---|---|---|
| Evidence first | Starting with a favorite method | Declares the question, estimand, population, grain, horizon, lineage, and claim boundary |
| Data readiness | Silently cleaning until a model runs | Preserves the source, profiles quality and privacy, and pauses on material choices |
| Adaptive analysis | Filling one fixed report template | Selects only the descriptive, diagnostic, predictive, or prescriptive work supported |
| Honest endpoints | Treating a recommendation as mandatory | Accepts an evidence request, negative validation, do_not_deploy, or bounded action |
| Shared uncertainty | Disturbing alternatives independently | Retains common time, market, participant, operational, campaign, or spatial shocks |
| Reproducible evidence | Separating prose from analysis | Links claims and accessible figures to JSON, CSV, hashes, and rerunnable code |
The contribution is not a newly invented statistical estimator. It is an adaptive orchestration system for evidence gating, method selection, claim control, dependent-risk handling, and case-specific analytical communication.
Quick install
npx skills add limingrui679-design/high-stakes-analytics-decision-lab -g
See runtime-specific, manual, and no-install options.
Overview · Complete workflow · Data gate · Four routes · Outputs · Real projects · Use
One complete evidence-to-decision workflow
flowchart TD
Q["1 · Frame the questiondecision · population · estimand · horizon"] --> S["2 · Establish the evidence contractsource · license · grain · lineage"]
S --> G{"3 · Data-readiness gate"}
G -->|"blocked"| X["Stoprequest corrected evidence"]
G -->|"confirmation required"| U["Appr
项目描述
A platform-neutral analytical Skill that profiles messy data, selects case-adaptive methods, and produces source-backed visual reports for high-stakes decisions.
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