singularity-forge/docs/architecture.md
Tom Boucher 59134fa426 docs: update documentation for v2.23 release features (#788)
New v2.23 features documented:

- getting-started.md: Add VS Code extension install section (chat participant,
  sidebar dashboard, command palette, RPC requirement)
- README.md: Add VS Code extension to documentation index, update troubleshooting
  link to include forensics
- docs/README.md: Add VS Code extension to user documentation table
- architecture.md: Add headless mode, MCP server mode, and VS Code extension to
  system structure diagram; expand Browser Tools description to cover 10 new tools
  (PDF export, device emulation, visual regression, structured extraction, route
  mocking, etc.); add missing extensions (Async Jobs, Remote Questions, TTSR,
  Universal Config)
- auto-mode.md: Add validate-milestone phase to the pipeline diagram and phase
  descriptions — reconciliation gate before milestone completion
- configuration.md: Add models.json resolution section — custom model definitions
  with ~/.gsd/agent/models.json and ~/.pi/agent/models.json fallback

Co-authored-by: TÂCHES <afromanguy@me.com>
2026-03-16 21:56:00 -06:00

7 KiB

Architecture Overview

GSD is a TypeScript application built on the Pi SDK. It embeds the Pi coding agent and extends it with the GSD workflow engine, auto mode state machine, and project management primitives.

System Structure

gsd (CLI binary)
  └─ loader.ts          Sets PI_PACKAGE_DIR, GSD env vars, dynamic-imports cli.ts
      └─ cli.ts         Wires SDK managers, loads extensions, starts InteractiveMode
          ├─ onboarding.ts   First-run setup wizard (LLM provider + tool keys)
          ├─ wizard.ts       Env hydration from stored auth.json credentials
          ├─ app-paths.ts    ~/.gsd/agent/, ~/.gsd/sessions/, auth.json
          ├─ resource-loader.ts  Syncs bundled extensions + agents to ~/.gsd/agent/
          └─ src/resources/
              ├─ extensions/gsd/    Core GSD extension
              ├─ extensions/...     12 supporting extensions
              ├─ agents/            scout, researcher, worker
              ├─ AGENTS.md          Agent routing instructions
              └─ GSD-WORKFLOW.md    Manual bootstrap protocol

gsd headless              Headless mode — CI/cron orchestration via RPC child process
gsd --mode mcp            MCP server mode — exposes tools over stdin/stdout

vscode-extension/         VS Code extension — chat participant (@gsd), sidebar dashboard, RPC integration

Key Design Decisions

State Lives on Disk

.gsd/ is the sole source of truth. Auto mode reads it, writes it, and advances based on what it finds. No in-memory state survives across sessions. This enables crash recovery, multi-terminal steering, and session resumption.

Two-File Loader Pattern

loader.ts sets all environment variables with zero SDK imports, then dynamically imports cli.ts which does static SDK imports. This ensures PI_PACKAGE_DIR is set before any SDK code evaluates.

pkg/ Shim Directory

PI_PACKAGE_DIR points to pkg/ (not project root) to avoid Pi's theme resolution colliding with GSD's src/ directory. Contains only piConfig and theme assets.

Always-Overwrite Sync

Bundled extensions and agents are synced to ~/.gsd/agent/ on every launch, not just first run. This means npm update -g takes effect immediately.

Fresh Session Per Unit

Every dispatch creates a new agent session. The LLM starts with a clean context window containing only the pre-inlined artifacts it needs. This prevents quality degradation from context accumulation.

Bundled Extensions

Extension What It Provides
GSD Core workflow engine — auto mode, state machine, commands, dashboard
Browser Tools Playwright-based browser automation — navigation, forms, screenshots, PDF export, device emulation, visual regression, structured data extraction, route mocking, accessibility tree inspection, and semantic actions
Search the Web Brave Search, Tavily, or Jina page extraction
Google Search Gemini-powered web search with AI-synthesized answers
Context7 Up-to-date library/framework documentation
Background Shell Long-running process management with readiness detection
Subagent Delegated tasks with isolated context windows
Mac Tools macOS native app automation via Accessibility APIs
MCPorter Lazy on-demand MCP server integration
Voice Real-time speech-to-text (macOS, Linux)
Slash Commands Custom command creation
LSP Language Server Protocol — diagnostics, definitions, references, hover, rename
Ask User Questions Structured user input with single/multi-select
Secure Env Collect Masked secret collection
Async Jobs Background command execution with async_bash, await_job, cancel_job
Remote Questions Discord, Slack, and Telegram integration for headless question routing
TTSR Tool-triggered system rules — conditional context injection based on tool usage
Universal Config Discovery of existing AI tool configurations (Claude Code, Cursor, Windsurf, etc.)

Bundled Agents

Agent Role
Scout Fast codebase recon — compressed context for handoff
Researcher Web research — finds and synthesizes current information
Worker General-purpose execution in an isolated context window

Native Engine

Performance-critical operations use a Rust N-API engine:

  • grep — ripgrep-backed content search
  • glob — gitignore-aware file discovery
  • ps — cross-platform process tree management
  • highlight — syntect-based syntax highlighting
  • ast — structural code search via ast-grep
  • diff — fuzzy text matching and unified diff generation
  • text — ANSI-aware text measurement and wrapping
  • html — HTML-to-Markdown conversion
  • image — decode, encode, resize images
  • fd — fuzzy file path discovery
  • clipboard — native clipboard access
  • git — libgit2-backed git read operations (v2.16+)
  • parser — GSD file parsing and frontmatter extraction

Dispatch Pipeline

The auto mode dispatch pipeline:

1.  Read disk state (STATE.md, roadmap, plans)
2.  Determine next unit type and ID
3.  Classify complexity → select model tier
4.  Apply budget pressure adjustments
5.  Check routing history for adaptive adjustments
6.  Dynamic model routing (if enabled) → select cheapest model for tier
7.  Resolve effective model (with fallbacks)
8.  Check pending captures → triage if needed
9.  Build dispatch prompt (applying inline level compression)
10. Create fresh agent session
11. Inject prompt and let LLM execute
12. On completion: snapshot metrics, verify artifacts, persist state
13. Loop to step 1

Phase skipping (from token profile) gates steps 2-3: if a phase is skipped, the corresponding unit type is never dispatched.

Key Modules (v2.19)

Module Purpose
auto.ts Auto-mode state machine and orchestration
auto-dispatch.ts Declarative dispatch table (phase → unit mapping)
auto-prompts.ts Prompt builders with inline level compression
auto-worktree.ts Worktree lifecycle (create, enter, merge, teardown)
complexity-classifier.ts Unit complexity classification (light/standard/heavy)
model-router.ts Dynamic model routing with cost-aware selection
model-cost-table.ts Built-in per-model cost data for cross-provider comparison
routing-history.ts Adaptive learning from routing outcomes
captures.ts Fire-and-forget thought capture and triage classification
triage-resolution.ts Capture resolution (inject, defer, replan, quick-task)
visualizer-overlay.ts Workflow visualizer TUI overlay
visualizer-data.ts Data loading for visualizer tabs
visualizer-views.ts Tab renderers (progress, deps, metrics, timeline)
metrics.ts Token and cost tracking ledger
state.ts State derivation from disk
preferences.ts Preference loading, merging, validation
queue-order.ts Milestone queue ordering