Skills

High Stakes Analytics Decision Lab

Build or review source-backed descriptive, diagnostic, predictive, and prescriptive...

Install

npx skills add limingrui679-design/high-stakes-analytics-decision-lab --skill high-stakes-analytics-decision-lab -g -a claude-code -y
Category
Data and ML
Updated
9d ago
License
MIT
Context cost
Mediumabout 2,077 tokens
Runs scripts
Yes, review before use

What it does

Build or review source-backed descriptive, diagnostic, predictive, and prescriptive analysis for consequential decisions. Use when an agent must profile and safely prepare uploaded data, turn a real dataset or research question into a reproducible study, investigate drivers without overstating causality, validate a model, compare feasible actions under dependent uncertainty and tail risk, trace every parameter to evidence and approval, or produce an answer-first analytical report across health, business, finance, policy, engineering, operations, behavioral science, AI, or planning.

High-Stakes Analytics & Decision Lab

Turn a real question into a defensible path from source evidence to analysis and, only when justified, bounded action. Keep observation, diagnosis, prediction, causal evidence, value judgments, and recommendation visibly separate.

Start here

Run the environment audit before an executable workflow:

python3 scripts/hsadl.py doctor

For a safe end-to-end setup example:

python3 scripts/hsadl.py demo --output-dir /absolute/path/to/demo

The demo is a synthetic engineering fixture. Never cite its values as empirical evidence.

Route before choosing a method

RoutePrimary questionValid endpoint
DescriptiveWhat is happening?Baseline report or evidence request
DiagnosticWhy might it be happening?Explanations to test with a visible causal boundary
PredictiveWhat is likely next?Validated prediction, negative validation, or do_not_deploy
PrescriptiveWhat should be done, if justified?Bounded action, pilot, diligence, evidence request, or no recommendation

When only a question is available, generate a blueprint instead of inventing results:

python3 scripts/hsadl.py route "How should limited review capacity be allocated?" \
  --scope full --output-dir /absolute/path/to/blueprint

Read references/analytics-triad.md and references/method-routing.md when a request is ambiguous or spans several routes.

Evidence-gated workflow

Read the whole SKILL.md on GitHub

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