Skip to main content

Features

Shipped, user-visible capabilities.

CLI

Interactive chat and one-shot run/skill commands with a persistent daemon that starts automatically and manages its own lifecycle. Sessions can be resumed by ID prefix or picked from history.

  • Model picker that queries provider APIs for available models
  • Fuzzy search and autocomplete for file paths, sessions, commands, and skills
  • File and directory attachments via @path
  • Slash commands and skill invocation
  • Engineering skills for structured workflows (plan, build, review)
  • Configurable locale
  • Multi-line input
  • Custom terminal renderer with React reconciler and structured output
  • Auto-update on startup with progress UI
  • Update flags to force or skip auto-update (--update, --no-update)
  • One-line install script

Agent execution

Single-pass lifecycle with four phases:

resolve → prepare → generate → finalize

The model runs once, effects apply inline, and the lifecycle completes. Explicit completion signals (done, no_op, blocked) let the caller distinguish outcomes.

  • Pre/post-tool-call effect pipeline (auto-install deps, format, lint)
  • Workspace profile detection with auto-detected install, lint, format, and test commands
  • Configurable model reasoning level (low, medium, high) with provider-specific mapping
  • Multi-provider support (OpenAI, Anthropic, Google, Vercel)
  • Provider rate limit awareness with sliding window pacing and exponential backoff
  • Proactive token budgeting with system prompt reservation and priority-based allocation
  • Step budget enforcement for cost protection
  • Two-tier result cache for read-only and search tools with cross-task persistence
  • Streaming progress output with real-time token usage
  • Inline task checklist for multi-step tasks

Tools

  • Find/search/read files with gitignore awareness
  • Edit/create/delete files
  • AST-based structural code editing with workspace-wide scope
  • Git status/diff/log/show/add/commit
  • Shell and test execution
  • Web search/fetch

Memory

On-demand memory toolkit (memory-search, memory-add, memory-remove) with three-scope persistent storage (session, project, user). Memory is not injected into the system prompt — the model searches for relevant context when it needs it.

  • Automatic observation via distiller with @observe directives
  • Semantic recall with embeddings and cosine similarity ranking
  • Hybrid retrieval scoring (cosine similarity + TF-IDF token overlap)
  • Topic tags on observations for filtered recall

Safety and control

  • Workspace sandbox boundary enforcement for filesystem access
  • Cooperative interruption and queued message handling

Diagnostics

  • Lifecycle trace with SQLite-backed indexed queries
  • Structured logs with level, session, and time filtering
  • Token usage reporting with prompt breakdown per turn
  • Status command with JSON output
  • Scoped debug logging with wildcard tag matching

Feature-flagged

Implemented but gated behind feature flags. See Configuration for setup.

  • AGENTS.md sync (syncAgents) — sync AGENTS.md into project memory for on-demand recall
  • Undo checkpoints (undoCheckpoints) — session-level undo via write-tool checkpoints
  • Parallel workspaces (parallelWorkspaces) — git worktree management and workspace-scoped sessions
  • Cloud sync (cloudSync) — portable memory and sessions across machines with EdDSA JWT auth