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An open-source method for governed agents

SpecForge blocks Claude Code from editing your code until you approve the spec and plan.

AI Transformation Lead

The method at a glance

Audit trail
Every approval on record
Lifecycle
Inception, Construction, Operations
Tests
15 shell test suites

The problem

By default, AI coding agents jump straight to code. Spec-driven tools make the agent write a spec and a plan first, then pause for a human to approve them. That pause is only advice, so a careful model stops and a hurried one runs past it. I built SpecForge so a check outside the model enforces that pause.

Constraints

  • The approval step had to block the edit itself, not ask the model to wait.
  • SpecForge had to work on brownfield code, the codebases teams already run.
  • Every approval had to leave a record in the repo.

What I built

  1. Joined GitHub Spec Kit's spec, plan and task pipeline with the approval gates of AWS AI-DLC, the AI-Driven Development Life Cycle.
  2. Wrote a PreToolUse hook, a check Claude Code runs before it edits a file. It blocks code edits until a person approves the spec and plan. It ignores projects that do not use SpecForge.
  3. Added a Ralph loop that works the approved task list on its own, one task at a time. It logs every step and stops at a blocker instead of guessing.
  4. Added a reverse-engineer command that reads an existing codebase and drafts its first specs.
  5. Wrote a Python generator that builds the same workflow for GitHub Copilot, Cursor, Gemini CLI and Codex. I have not yet verified any of those four against a live install.
  6. Wrote 15 shell test suites that GitHub Actions runs on every pull request and every push to main.
  7. Built SpecForge's own Operations phase with SpecForge. Its spec, plan and audit trail sit in the repo.

Languages

  • Shell
  • Python

Stack

  • Claude Code plugin
  • PreToolUse hooks
  • GitHub Spec Kit
  • AWS AI-DLC
  • GitHub Actions

Code and links

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