Open source · Apache-2.0 · v0.7.0

Give AI less to rediscover.
Give engineering more evidence.

FORGE is a credit-aware control layer for deliberate, governed AI-assisted software development. It prepares repository facts locally, bounds context, classifies risk, plans work, preserves approvals, and records verification evidence before the model spends deeper reasoning.

Install FORGE View release
36/36 release tests SHA-256 verified assets Sigstore provenance Node 20+
FORGE terminal-style overview: prepare context, govern execution, verify with evidence
WHY FORGE

Models should reason about the change — not repeatedly reconstruct the repository.

FORGE moves deterministic preparation out of the model loop. The coding agent still writes and reasons; FORGE gives it a cleaner operating boundary.

01

Bounded context

Inspect repository facts and select only relevant context instead of feeding the entire project into every task.

02

Risk-aware planning

Classify work, activate proportional engineering capabilities, and surface approval points for sensitive changes.

03

Reusable work packets

Cache deterministic preparation so repeated work can avoid unnecessary repository rediscovery when context has not changed.

04

Evidence, not vibes

Track run state, validation, verification and privacy-preserving efficiency telemetry instead of treating a chat transcript as the only execution record.

INSTALL

From release to forge --version.

The v0.7.0 GitHub release ships checksum-verifying installers for Linux/macOS and Windows PowerShell. npm registry publication is separate and is not claimed here.

1 · Download, verify and install

curl -fsSLO https://github.com/gODtECH-Ctl-Create/gODtECH-FORGE/releases/download/v0.7.0/install.sh
sh install.sh 0.7.0
forge --version

2 · Initialize inside your project

forge init --dry-run
forge init
forge doctor
forge validate
REAL INSTALL VALIDATION

The install path was tested outside the FORGE repository.

Historical v0.6.0 installation evidence: condensed captures from the first real Windows and Codespaces/Linux sessions. Current installation commands above target v0.7.0; these original captures do not represent new v0.7.0 device tests.

Windows PowerShell · verified
PS C:\Users\User> Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass
PS C:\Users\User> .\install.ps1 -Version 0.6.0
Downloading FORGE 0.6.0...
Checksum verified. Installing FORGE 0.6.0...

added 5 packages in 18s
FORGE 0.6.0 installed successfully.
PS C:\Users\User> forge --version
0.6.0
PS C:\Users\User> node --version
v24.18.0
GitHub Codespaces · verified
$ curl -fsSLO .../v0.6.0/install.sh
$ sh install.sh 0.6.0
Downloading FORGE 0.6.0...
Checksum verified. Installing FORGE 0.6.0...

added 5 packages in 2s
FORGE 0.6.0 installed successfully.
$ forge --version
0.6.0
$ forge doctor
✓ Node.js 24.20.0 is supported.
✓ Git repository detected.
OPERATING MODEL

Intent → context → reasoning → evidence → ship.

01

Prepare

forge prepare --task "..."

Repository facts, bounded context, risk, discovered commands and remaining model work.

02

Plan

forge plan --task "..."

Proportional capabilities, approvals, workflow and ordered engineering steps.

03

Run

forge run start --task "..."

Persist resumable execution state instead of losing the workflow inside one conversation.

04

Measure

forge metrics

Local preparation telemetry: cache reuse, latency, deterministic work and context-reduction estimates.

AI CLIENT INTEGRATION

Provider-neutral over MCP.

FORGE exposes deterministic preparation and run state through a local stdio MCP server. The AI coding client remains responsible for model execution.

forge mcp serve
EVIDENCE LAB

We test the claim before we market the claim.

The exploratory DeployGuard phase (DG-BM-001 through DG-BM-005) is complete. FORGE telemetry remains separate from provider billing; controlled comparisons have not started. Read the phase summary or follow controlled benchmarking in issue #49.

PILOT · DG-BM-001

DeployGuard incident CRUD

Plain AI control vs FORGE-assisted implementation of PostgreSQL-backed incident management.

Read benchmark
28.6%fewer unique files inspected7 → 5
0FORGE implementation retriescontrol: several
3/3tests passedboth runs
74.7%estimated context reductionFORGE internal metric
What this does not prove: DG-BM-001 was a pilot, not a clean controlled trial. Starting commits differed, the control could read FORGE-generated project files, Docker verification was not equal, and provider token/cost data was unavailable. The 74.7% figure is a FORGE context-selection estimate — not a claim of 74.7% credit savings.
MILESTONE 2

Controlled multi-task benchmarks

Same baseline commit, same task brief, same acceptance criteria and explicit separation between measured behavior, FORGE estimates and provider billing data.

View protocol
DG-BM-002authentication / securityexploratory complete
DG-BM-003database migrationexploratory complete
DG-BM-004GitHub Actions CI/CDexploratory complete
DG-BM-005Kubernetes / probesexploratory complete
GODTECH ECOSYSTEM

Three tools. Three clear responsibilities.

FORGE orchestrates and governs. StackPilot creates production-minded project foundations. Steward keeps existing repositories healthy. They remain independently usable and connect through public contracts.

01

FORGE

Prepare context, classify risk, plan work, govern approvals, persist runs and collect evidence.

Current product →
02

StackPilot

Generate supported project structures and golden paths without making scaffolding part of FORGE.

Explore StackPilot →
03

Steward

Scan repository health deterministically, expose findings, and apply only explicit safe fixes.

Install Steward →
Integration boundary: FORGE may invoke Steward when repository-health evidence or safe maintenance is relevant. StackPilot may consume Steward's versioned scan result observationally. Neither relationship makes Steward or StackPilot a runtime prerequisite for FORGE.
SAFETY BOUNDARIES

More capable does not mean less controlled.

Secret-like paths excluded from generated work packets.
Higher-risk work can require explicit human checkpoints.
Discovered commands are reported, not silently executed.
Application technology choices remain with the consuming project.
Completion should be backed by repository evidence.
Metrics avoid task text, source code and repository identity.
START WITH YOUR REPOSITORY

Prepare locally. Reason proportionally. Ship with evidence.

Install v0.7.0Explore GitHub