Design agent system prompts, parallel architectures, and methodological guardrails for data science decision-packs. Use when creating orchestrator, subagent, or parallel agent systems for analytical workflows. Covers anti-fabrication rules, epistemic…
decision-lab house figure style for matplotlib. Use whenever creating, styling, or saving any matplotlib figure, chart, or plot. The environment is already styled — this skill covers only the rules the style config cannot enforce.
Complete reference for decision-lab (dlab). Use when the user asks about creating decision-packs, designing data science agents, running sessions, analyzing results, or anything related to dlab CLI, agent architecture, parallel subagents, or decision-pack…
Guide a human through creating a dlab decision-pack by asking questions and then calling generate_dpack(). Use this skill whenever the user wants to create, set up, or scaffold a new decision-pack, agent environment, or Docker-sandboxed config for dlab — even…
How to create a dlab decision-pack directory using generate_dpack() from Python code
Methodology for probabilistic forecasting of when and whether a future event will occur. Covers Bayesian survival models, reference class reasoning, driver threshold models, leading indicator models, scenario decomposition, and causal mechanism models. Use…
Navigate and analyze completed dlab session directories. Use when pointed at a work directory to understand what happened during a run — explore logs, outputs, parallel agent results, and the skills/prompts that shaped the analysis.
Visual language and UX patterns for Textual TUI applications in dlab