Deterministic tooling for AI-assisted software delivery.

We build tools that make agent work:

• governed — specs, decisions, and execution live in reviewable artifacts
• traceable — changes can be linked back to why they happened
• phase-aware — implementation, verification, and stability are explicit
• local-first — the CLI and repo remain the control plane

govctl is a governance-as-code CLI for teams using AI to build software seriously.

It gives AI-assisted development a control plane in the repository:

• RFCs say what must be true
• ADRs record why a design was chosen
• Work items track execution and acceptance criteria
• Verification guards enforce executable completion gates

Typical flow:

govctl init
govctl status
govctl rfc new "Caching Strategy"
govctl adr new "Choose cache backend"
govctl work new --active "implement caching"

Highlights:

• spec-first, phase-gated workflow
• stable CLI contract for humans and agents
• brownfield adoption through the /migrate workflow for agent-guided governance onboarding
• governed artifact operations through list, show, get, edit, and lifecycle verbs

skillc helps skill authors and power users scaffold, validate, compile, search, and analyze Agent Skills.

Typical flow:

skc init my-skill
skc lint my-skill
skc build my-skill
skc stats my-skill

Highlights:

• local authoring and validation
• searchable compiled skill content
• usage analytics and sync
• MCP integration for read-side agent workflows

These are active directions we are exploring, not yet stable public products:

• jjgov — multi-agent collaboration workflows around Jujutsu
• everevolve — project rules inferred and refined from commit history

We believe AI coding gets more useful when it is:

• structured enough to review
• explicit enough to automate
• disciplined enough to scale

The goal is not more ceremony. The goal is to turn fast generation into reliable delivery.

_{Built with phase discipline. Governed by govctl.}