projects / hkit
hkit
Spec-driven AI Engineering Framework
roleDesign and implementation
What it is
hkit is an additive framework around GitHub Spec Kit. It connects specification, clarification, planning, task breakdown, implementation, review, architecture decisions, verification, and delivery across Claude Code, Codex, and other coding agents. It is not an official GitHub Spec Kit fork and does not imply upstream endorsement.
The problem
Long AI coding sessions can produce changes that are hard to review, test, or hand off. hkit structures the work into planned stages with human gates and evidence-based outputs.
My role
Design and implementation
What I worked on
- Built specification, planning, implementation, review, and delivery workflows.
- Added behavioral quality gates and negative controls.
- Created architecture decision record capture.
- Implemented review routing and agent handoffs.
- Added session hooks and worktree isolation.
- Shared instructions across coding agents.
- Built Markdown to HTML/PDF delivery with Mermaid diagrams.
- Supported Arabic RTL output and redacted client deliverables.
Decisions and trade-offs
Additive around Spec Kit
The framework wraps untouched upstream Spec Kit assets rather than forking or modifying them.
Human gates at each stage
Specification, planning, implementation, and delivery each have explicit review points outside the model's judgment.
Evidence-based handoffs
Each stage produces artifacts that the next stage can verify against, not just chat history.
Testing and verification
- Behavioral quality gates and negative controls on agent outputs.
- Review routing before changes are accepted.
- Structured handoff artifacts between workflow stages.
How it fits together
Human gates
Agent tools
Claude Code · Codex · MCP · Skills · Hooks · Worktrees
Additive framework around GitHub Spec Kit (not an official fork)Tools and workflow
Workflow
Agent tooling
Output
Status and links
Private personal project. No public repository link at this time.