GitHub Spec Kit
Converts plain-language AI agent briefs into complete development packages.
A repeatable, auditable path from AI concept to development-ready specification. No technical translation required.
View the Specification ↓What It Does
Define requirements with user stories, acceptance criteria, and functional requirements — structured for engineering handoff.
Generate implementation plans with technical architecture and phasing strategy — giving teams a clear roadmap before a single line is written.
Break specifications into actionable work items with acceptance criteria — so every task has a clear definition of done.
Demonstration
To demonstrate this workflow, a Chief Estimator Risk Agent brief was run through the full GitHub Spec Kit process. The result is a complete specification for an agent that queries SharePoint historical estimate data and generates executive-ready conceptual risk briefings.
The output package includes the agent file, prompt file, output contract, and validation rubric — along with a live example risk assessment for a USD 285M Regional Acute Care Hospital Expansion project in Phoenix, Arizona. The assessment surfaces 9 estimate risks with historical evidence, likelihood and impact ratings, and mitigation strategies.
Project Documentation
The complete specification package — from requirements through implementation tasks.
Complete requirements, user stories, and acceptance criteria for the Risk Estimation Agent system.
Live demonstration for a USD 285M Regional Acute Care Hospital Expansion — executive-ready output with 9 risks, evidence, and mitigations.
Background research, technology decisions, and design rationale behind the Risk Estimation Agent.
Technical architecture, phasing strategy, and development approach for building the agent.
Entity definitions, relationships, and data structures powering the Risk Estimation Agent system.
How to get started with the Risk Estimation Agent — step-by-step setup instructions.
Detailed breakdown of all work items and deliverables with acceptance criteria for each task.
About
This methodology reflects the approach applied in a large-scale enterprise AI program to assess and govern 70 AI use cases. It gives non-engineering leaders a repeatable, auditable path from AI concept to development-ready specification — without requiring technical translation at every step.
GitHub Spec Kit is free and open source. Fork it, adapt it, and use it to bring structure to your own AI development programs.