chihlasm/resolutionflow
1
0
Fork 0
Code Issues 23 Pull Requests 1 Actions Packages Projects Releases Wiki Activity

[Feature] Tree Effectiveness Dashboard #61

New Issue
Closed
opened 2026-02-10 16:00:00 +00:00 by chihlasm · 1 comment
chihlasm commented 2026-02-10 16:00:00 +00:00 (Migrated from github.com)
Copy Link

Summary

A dashboard showing: most-used trees, average resolution time per tree, completion rate, escalation rate, most-common paths taken (heatmap on tree visualization), and trees with high custom-step insertion (signals missing content).

Why

  • MSP managers have zero visibility into troubleshooting quality today
  • Sells the product to decision-makers (not just engineers) — expands buyer persona
  • Answers: "Which trees need improvement?" and "Which engineers need training?"
  • Turns ResolutionFlow from an engineer tool into a management tool

Depends On

  • #56 Step-Level Time Tracking + Session Outcomes (foundational data)

Implementation Notes

  • Aggregation queries on sessions table (group by tree_id, compute stats)
  • Dashboard UI: cards with key metrics, sortable table, tree heatmap visualization
  • Metrics: usage count, avg resolution time, completion rate, escalation rate, custom step frequency
  • Cache aggregates (recompute daily or on-demand)
  • Trees with high custom-step insertion = signal for missing content (flag for authors)

Key Metrics

Metric Source Value
Most used trees sessions.tree_id count Adoption signal
Avg resolution time completed_at - started_at Efficiency
Completion rate completed / total sessions Tree quality
Escalation rate outcome = 'escalated' Training gaps
Custom step frequency custom_steps array length Missing content
Path heatmap path_taken aggregation Branch optimization

Sources

  • .claude/docs/ai/resolutionflow/10x/session-1.md — Medium Opportunity #2
  • docs/plans/2026-02-04-feature-ideas-brainstorm.md — Ideas 5, 9 (Path Analytics, Tree Health)

Priority

Explore — high value, needs outcome data foundation first

## Summary A dashboard showing: most-used trees, average resolution time per tree, completion rate, escalation rate, most-common paths taken (heatmap on tree visualization), and trees with high custom-step insertion (signals missing content). ## Why - MSP managers have zero visibility into troubleshooting quality today - Sells the product to decision-makers (not just engineers) — expands buyer persona - Answers: "Which trees need improvement?" and "Which engineers need training?" - Turns ResolutionFlow from an engineer tool into a management tool ## Depends On - #56 Step-Level Time Tracking + Session Outcomes (foundational data) ## Implementation Notes - Aggregation queries on sessions table (group by tree_id, compute stats) - Dashboard UI: cards with key metrics, sortable table, tree heatmap visualization - Metrics: usage count, avg resolution time, completion rate, escalation rate, custom step frequency - Cache aggregates (recompute daily or on-demand) - Trees with high custom-step insertion = signal for missing content (flag for authors) ## Key Metrics | Metric | Source | Value | |--------|--------|-------| | Most used trees | `sessions.tree_id` count | Adoption signal | | Avg resolution time | `completed_at - started_at` | Efficiency | | Completion rate | completed / total sessions | Tree quality | | Escalation rate | outcome = 'escalated' | Training gaps | | Custom step frequency | `custom_steps` array length | Missing content | | Path heatmap | `path_taken` aggregation | Branch optimization | ## Sources - `.claude/docs/ai/resolutionflow/10x/session-1.md` — Medium Opportunity #2 - `docs/plans/2026-02-04-feature-ideas-brainstorm.md` — Ideas 5, 9 (Path Analytics, Tree Health) ## Priority **Explore** — high value, needs outcome data foundation first
chihlasm commented 2026-03-21 15:24:42 +00:00 (Migrated from github.com)
Copy Link

Completed — FlowPilot Analytics page provides metrics on resolution rates, confidence tiers, escalation rates, and flow effectiveness.

Completed — FlowPilot Analytics page provides metrics on resolution rates, confidence tiers, escalation rates, and flow effectiveness.
Sign in to join this conversation.
No Branch/Tag Specified
Branches Tags
Labels
Clear labels
10x-analysis
From 10x product analysis
 backend
FastAPI/Python work
 bug
Something isn't working
 collaboration
Team sharing, escalation, notifications
 database
PostgreSQL/schema changes
 documentation
Documentation updates
 duplicate
This issue or pull request already exists
 enhancement
Improvement to existing feature
 feature
New functionality
 frontend
React work
 good first issue
Good for newcomers
 help wanted
Extra attention is needed
 integration
PSA, external service integrations
 intelligence
Analytics, AI, data-driven features
 invalid
This doesn't seem right
 priority: high
Do this soon
 priority: low
Nice to have
 priority: medium
Important but not urgent
 question
Further information is requested
 quick-win
Low effort, high value
 strategic
Long-term strategic bet
 ux
User experience improvements
 wontfix
This will not be worked on
No Label 10x-analysis backend feature frontend intelligence priority: medium
Milestone
No items
No Milestone
Projects
Clear projects
No project
Assignees
Clear assignees
chihlasm
No Assignees
1 Participants
Notifications
Due Date
No due date set.
Dependencies

No dependencies set.

Reference: chihlasm/resolutionflow#61
Delete Branch "%!s()"

Deleting a branch is permanent. Although the deleted branch may continue to exist for a short time before it actually gets removed, it CANNOT be undone in most cases. Continue?