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gv-exp-specwright

AI-native enterprise documentation platform. Living specs that generate tickets, AI agents that maintain docs, repo-native knowledge that replaces Confluence.

Status

Stage: Brief Started: 2026-02-06 Timebox: 4 weeks (2 concierge + 2 prototype) Budget: $500

Hypothesis

We believe that engineering orgs (50-500 devs) will replace Confluence with a repo-native documentation platform because AI agents can keep docs alive automatically, and structured specs that generate tickets and track implementation progress are more valuable than static wiki pages.

Links

Quick Start

# Clone
git clone git@github.com:Gerner-Ventures/gv-exp-specwright.git
cd gv-exp-specwright

# Install all dependencies (backend + frontend)
make install

# Run tests
make test

# Run backend + frontend dev servers in parallel
make dev

Make Commands

Run make help for the full list. Highlights:

Command Description
make install Install backend + frontend dependencies
make dev Run FastAPI dev server with Doppler secrets on :3000
make test Run Python test suite
make lint Lint backend (ruff) + frontend (eslint)
make format Auto-fix and format Python code
make typecheck Run mypy + vue-tsc type checks
make build Build Vue SPA for production
make build-docker Build production Docker image
make docker-dev Run dev Docker image with source mounts
make helm-template Render Helm chart locally
make clean-all Remove all build artifacts + Docker images

Dev Environment (K8s)

Each developer gets an isolated environment on the shared DOKS cluster via DevSpace.

Prerequisites

One-time setup

doppler login
doctl auth init
doctl registry login                                      # DOCR auth
doctl kubernetes cluster kubeconfig save gv-shared        # kubeconfig

Daily workflow

export DEVSPACE_USERNAME=ng   # or set in .envrc

devspace dev                  # build, deploy, sync, port-forward
# → http://localhost:3000     (port-forwarded)
# → https://ng.specwright.gernerventures.com (ingress, after DNS setup)

devspace run logs             # tail pod logs
devspace run sync-secrets     # re-sync Doppler secrets
devspace run sync-trigger     # manually run reverse sync cron
devspace purge                # tear down dev environment

File changes in src/, templates/, and static/ sync into the pod and uvicorn auto-reloads.

See docs/self-hosting.md for production deployment and more details.

Architecture

Three-tier platform vision:

Tier What Status
Repo Agents Per-repo spec parsing, PR analysis, doc maintenance, ticket sync v0.1 target
Agent Mesh Cross-repo impact analysis, conflict detection, dependency mapping Future
Org Brain Cross-repo search, ownership graph, decision index, onboarding gen Future

Tech Stack

Component Technology
Backend Python 3.12+, FastAPI, uvicorn
Agent runtime Anthropic Python SDK (Claude)
Spec parser Custom markdown parser + python-frontmatter
Ticket sync Jira REST API / Linear GraphQL API / GitHub Issues
Web UI Vue 3, Vite, Tailwind CSS, Pinia
Hosting Self-hosted K8s (DigitalOcean) via Helm chart
Secrets Doppler
Dev tooling DevSpace

Project Structure

src/specwright/
  main.py              # FastAPI app: webhook routes, health checks
  settings.py          # Pydantic Settings (env vars)
  github/              # GitHub App webhook handling
  agent/               # Claude agent runtime
  parser/              # Spec markdown parser + writer
  sync/                # Ticket sync engine + adapters
  config/              # SPECWRIGHT.yaml parser
  cron/                # Reverse sync cron job
  web/                 # Web routes (serves Vue SPA + Jinja2 fallback)
  cli.py               # CLI entrypoint
  mcp/                 # MCP server
frontend/              # Vue 3 SPA (Vite + Tailwind + Pinia)
tests/                 # pytest tests
templates/             # Jinja2 HTML templates (fallback)
static/                # CSS/JS/images + built SPA (static/app/)
chart/specwright/      # Helm chart for K8s deployment

Current Metrics

Metric Target Current
PM spec adoption 60% -
Doc freshness 70% -
Engineer engagement 40% -
PM time saved 3 hrs/wk -
Question answer quality 70% -

Metadata

Release files for gv-specwright 1.15.0

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Source distribution for gv-specwright 1.15.0
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gv_specwright-1.15.0-py3-none-any.whl Python 3 none any Details

Total release size: 14.3 MB

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