horizon-track

# Horizon Track Track long-running objectives that span multiple sessions, days, or weeks. ## When to use When an objective is too large for a single session — multi-week features, research programs, migration projects, or any work that requires persistent progress tracking across conversations. ## Steps 1. **Initialize horizon** — define the objective, target date, and 3-7 milestones 2. **Store horizon** — call `mcp__plugin_ruflo-core_ruflo__memory_store` with namespace `horizons` and key `horizon-[name]`: ```json { "objective": "...", "created": "2026-04-28", "targetDate": "2026-05-15", "milestones": [ {"id": "m1", "name": "...", "criteria": "...", "status": "pending"}, {"id": "m2", "name": "...", "criteria": "...", "status": "pending"} ], "currentMilestone": "m1", "sessions": [] } ``` 3. **Session check-in** — at the start of each session: - Recall horizon: `mcp__plugin_ruflo-core_ruflo__memory_retrieve` key `horizon-[name]` namespace `horizons` - Review milestone status - Assess drift (are we still on track?) - Plan this session's contribution 4. **Work and record** — as work progresses: - Update milestone status - Record session summary - Store intermediate findings 5. **Session check-out** — at the end of each session: - Update horizon state in memory - Record what was accomplished - Note blockers or scope changes - Estimate remaining effort 6. **Milestone completion** — when a milestone is done: - Verify completion criteria met - Store learned patterns via `mcp__plugin_ruflo-core_ruflo__hooks_intelligence_pattern-store` - Advance to next milestone 7. **Drift detection** — flag when: - Progress rate suggests target date will be missed - Scope has grown beyond original definition - Dependencies have changed - Approach needs fundamental rethinking ## Memory namespaces - `horizons` — active horizon definitions and state - `horizon-sessions` — per-session summaries keyed by `[horizon]-[date]` - `horizon-learnings` — patterns and insights discovered during the horizon