windags-sensemaker

Classify raw problem descriptions into structured ProblemUnderstanding payloads for downstream agents.

2|Updated Feb 11, 2026
One-click install
npx skills add https://github.com/curiositech/port-daddy --skill windags-sensemaker
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: windags-sensemaker
Source: https://github.com/curiositech/port-daddy/tree/main/skills/windags-sensemaker
Command: npx skills add https://github.com/curiositech/port-daddy --skill windags-sensemaker

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

WinDAGs Sensemaker classifies and validates problems to produce a structured ProblemUnderstanding for downstream agents, guiding decomposition and execution planning.

Core Features & Use Cases

  • WinDAGs Sensemaker performs problem classification to determine if a problem is well-structured, ill-structured, or wicked.
  • It extracts principal parts: unknown, data, conditions, and output_type for precise downstream planning.
  • It conducts validity assessment (clarity, feasibility, coherence) and computes an overall planning budget.
  • It provides domain routing recommendations (primary/secondary domains) and a meta-skill suggestion.
  • It includes a halt readiness mechanism to generate clarifying questions when necessary.
  • It emits a complete ProblemUnderstanding payload suitable for a Decomposer.

Quick Start

Feed a raw problem description into WinDAGs Sensemaker to obtain a structured ProblemUnderstanding.

Frequently Asked Questions about windags-sensemaker

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I classify raw problems into structured understandings for downstream agents?

Problem classification categorizes a raw problem as well-structured, ill-structured, or wicked. It evaluates clarity, feasibility, and coherence to produce validity scores and a halt readiness mechanism for ill-defined inputs.

What is problem decomposition and validity assessment in AI orchestration?

Problem decomposition and validity assessment evaluate clarity, feasibility, and coherence to compute an overall planning budget. This process prevents downstream execution failures by halting ambiguous inputs and emitting clarifying questions.

How do I extract principal parts like unknowns and conditions from problem descriptions?

Extract principal parts like unknowns and conditions by processing problem descriptions through a classification pipeline. This identifies the unknown, data, conditions, and output type required for precise downstream execution planning.

When do I need a halt-gate mechanism for problem analysis pipelines?

You need a halt-gate mechanism for problem analysis pipelines when validity assessment detects insufficient clarity, feasibility, or coherence. It halts downstream processing and generates clarifying questions to refine the raw problem input.

Does domain routing work with problem classification for multi-domain orchestration?

Domain routing works with problem classification by assigning primary and secondary domains to a parsed problem. It generates routing recommendations and meta-skill suggestions to direct the payload to the correct downstream processing path.