Features
Capability map
| Area | What you get |
|---|---|
| Task tracking | Beads (bd) — Dolt-backed issues with dependencies, status, history; survives context resets |
| Code memory | graphify (structural graph) + cocoindex-code (semantic RAG) + .claude/memory/ facts |
| External docs | context7 MCP — live, version-correct library documentation |
| Version control | Choose git, svn, or none at setup |
| Remote host | GitHub, GitHub Enterprise, GitLab, self-managed GitLab, Bitbucket, Forgejo, Gitea, or a custom URL — token-based |
| Host MCP | The matching git-host MCP is wired automatically per remote type |
| Models | Claude (API key or OAuth) + optional Ollama local models, selectable & auto-installed |
| Model routing | claude-code-router sends easy/background work to cheap/local models |
| Agents | 5 delivery + 9 audit/checker + 1 brownfield specialist subagents |
| Autonomy | Ralph loop (interactive / headless / containerised / CI) |
| Quality | Google style, conventional commits, format/lint/test git hooks, architect+quality-gate review, static analysis on every change, objective metric targets (0 new smells/duplicates, 0 warnings), >80 % coverage + BDD E2E gates, leveled logging, .http files for REST endpoints, DB rules §3c (3NF+FKs for new schemas, brownfield schemas handled with care) |
| Branching | simple / gitflow / none, PR-only, auto-release, SemVer/CalVer |
| Team | shared issue DB, atomic claim, session-start auto-pull, pull-before-push, shared preferences |
| Token savings | caveman + rtk on by default, graph/RAG retrieval, cost routing |
Advantages in depth
Better memory, fewer hallucinations
Two complementary code indexes plus durable task memory mean the agent looks things up instead of guessing or re-reading dozens of files. See Memory.
Big token reduction
- caveman — terse output mode (~75% fewer output tokens; code/commits/security stay normal).
- rtk — filters/compresses verbose command output before it enters context (60–90% fewer).
- graph + RAG retrieval — answer from graphify/cocoindex instead of reading whole files (~70% fewer).
- model routing — send easy/background steps to cheap or local (Ollama) models.
- measure first —
aiflow cost(ccusage) shows real spend.
Team-ready by design
Issues live in a shared Dolt database that syncs over your git remote — one issue graph for the whole team, no extra server. Atomic claiming prevents two people grabbing the same task; pull-before-push prevents clobbering. See Team collaboration.
Governed & auditable
Conventional Commits, enforced Google style, a review gate against acceptance criteria, security/quality/deps/test/perf/docs audits, and a real branching + release model. See Workflows.
Autonomous when you want it
The Ralph loop finishes a task unattended — locally, in a container, or in CI — and stops at
COMPLETE/BLOCKED, writing result.json.
Yours, not a hub
Everything runs on your keys/tokens and your infrastructure; secrets never leave the project.
The bundled toolchain
Each tool earns its place by raising quality, cutting token cost, or making delivery
autonomous and auditable. See the full list and links in Feedback & contributing → Credits.
Install only what your config enables with aiflow install-deps (--all = full set).