Get ecosystem-aware next task recommendation
Analyzes ecosystem context to recommend the optimal next task with rationale and impact.
/plugin marketplace add Data-Wise/rforge/plugin install data-wise-rforge@Data-Wise/rforgeGet intelligent recommendations for what to work on next based on ecosystem context.
Uses the rforge_next MCP tool to:
# Get next task
/rforge:next
# Next task for specific package
/rforge:next medfit
# Next task with context
/rforge:next --context "Before release"
Returns task recommendation with:
š NEXT TASK RECOMMENDATION
Task: Fix bug #234 - segfault in extract_mediation
ID: T-2025-01-15-002
Package: medfit
Priority: HIGH
Why now:
ā¢ Blocking probmed release
ā¢ Affects 2 packages
ā¢ CRAN submission waiting
ā¢ High user impact
Estimated time: 2-3 hours
Context:
ā¢ 3 GitHub issues reference this
ā¢ Already has test case
ā¢ Fix will unblock 2 downstream releases
Recommendation: Work on this immediately
š NEXT TASK RECOMMENDATION
Task: Add bootstrap confidence intervals
ID: T-2025-01-15-001
Package: medfit
Priority: MEDIUM
Why now:
ā¢ No urgent blockers
ā¢ Good time for feature work
ā¢ Complements recent changes
ā¢ Low ecosystem impact
Estimated time: 4-6 hours
Context:
ā¢ Requested by 3 users
ā¢ Aligns with v2.2.0 roadmap
ā¢ Can be done without cascade
Alternative tasks:
ā¢ Update documentation (1 hour, quick win)
ā¢ Research weighted mediation (exploratory)
š NEXT TASK RECOMMENDATION
Context: Before Release
Task: Complete documentation updates
ID: DOC-SWEEP
Priority: HIGH (release blocker)
Checklist:
ā NEWS.md updated
ā README examples (2 outdated)
ā Vignette cross-refs (3 packages)
ā API documentation (1 function)
Estimated time: 1.5 hours
Why now:
ā¢ Release planned for next week
ā¢ All code changes complete
ā¢ CRAN requires current docs
ā¢ Quick wins available
Recommendation: Focus on docs before release
/rforge:capture - Add new tasks/rforge:complete - Mark tasks done/rforge:status - See overall health/rforge:impact - Understand task impact/nextSmart increment transition - auto-close current if ready, intelligently suggest next work (backlog or new feature)