Momentum keeps your project’s memory and state as Markdown files in the repo — so every session your agent retrieves the right context, hallucinates less, and turns a vague request into a plan that’s far better grounded: what to change, where, and how.
init asks which agent to set up — or pass --agent claude-code | codex | opencode | antigravity
Ask an agent to fix a bug and it greps around, fills the gaps with assumptions, and drafts a plan on shaky ground — burning tokens rediscovering what your project already knew. Momentum hands it the project’s real state up front, so it reasons from facts instead of guesses.
The state lives with the project, so the agent starts every task already knowing what matters.
Your agent reasons from recorded facts — status, decisions, history — instead of confident guesses. Fewer wrong turns, fewer retries.
The relevant history and prior decisions surface first — not whatever a blind search returned. Less noise in the window, less token waste.
A vague ask becomes a concrete plan — what to change, where in the codebase, how to verify. Not infallible, but anchored in real project state instead of a guess.
Based on hands-on use — momentum reduces guesswork and re-derivation. Your mileage will vary by project and agent.
Every phase moves through the same five stages. Your agent drives all of it — and stops only at the one gate that matters: the merge and release.
Across days, branches, and sessions — the building blocks your agent uses to never lose the thread.
Plan, execute, verify, release. Every phase is a unit of work with its own brainstorm, plan, tasks, and history.
Bugs, features, tech debt, and enhancements — with priorities and per-item context the agent files itself.
Append-only log of decisions, discoveries, and scope changes. The “why” outlives any single session.
Thirteen autonomous agent rules — orient first, verify before claim, log every decision. No enforcement overhead.
Slash commands your agent runs automatically — start, complete, sync, review, validate.
Coordinate multiple related projects from one agent session — opt-in, additive, zero extra setup by default.
Momentum isn’t a framework or a service. It’s .md files and conventions your AI IDE picks up the moment it opens your repo.
Your agent’s instruction file, a specs/ folder, rule & command definitions, and git hooks — straight into your repo.
Your AI IDE already loads that instruction file every session. Momentum fills it with a structured workflow and a map of where state lives.
Reads status.md to orient, logs to history.md, tracks work in backlog.md. Automatically.
Every file is Markdown in the Open Knowledge Format (OKF) — so your project’s context stays portable, human-readable, and interoperable across tools instead of locked to one vendor.
Fully compatibleThe agent proceeds silently unless interrupted — but every group commits cleanly, every decision lands in history, and the only hard stop is the merge and publish. Those are yours to approve.
Phases, backlog, history, doc-sync — all run as slash commands. The three you’ll reach for most:
Thirteen autonomous behaviors your agent follows in the background. Three of the highest-leverage:
Feature branch auto-created. Conventional commits. Push silently. Never merge to main without your explicit OK.
Every meaningful decision, discovery, or scope change lands in history.md the moment it happens. The “why” outlives every session.
No completion without evidence. Run the test, read the output, mark done only if it passes. Closes the “should work now” failure mode.
Single-project is the default — zero extra setup. When related repos need to coordinate, three layers let one agent session work across all of them.
Drive a whole cross-project feature end-to-end from one session. Conductor + per-project supervisors, wave-ordered, multi-hour. Survives session kill via disk-only resume.
Four single-step verbs the agent runs per task. One move and done — no persistent state, no waves.
Durable substrate both tiers above read and write: ecosystem.json members + dependency edges, initiatives/ feature tracking, and a daily session log.
Your project doesn’t forget what it was building when you stepped away for a week. Pick up exactly where you left off, with the agent already oriented.
Bring discipline to agentic AI work across your team. Every decision logged, every phase planned, every release tagged — without enforcement overhead.
Read the why behind every decision your engineers’ agents make. Phases, decisions, and history are first-class artifacts — not lost in chat transcripts.