Team Analysis

Team Analysis connects to your Jira or Azure DevOps board and produces a comprehensive analysis of your team's real delivery patterns. The analysis becomes a reusable profile that calibrates future planning sessions.

What gets analyzed

CategoryDetails
VelocityPer-sprint velocity, team average, per-developer breakdown with delivery vs KTLO split
Sprint CadenceSprint length, seasonal patterns, velocity trends over time
Story StructureAverage stories per epic, story point distribution, typical story size
Task PatternsAverage tasks per story, type distribution (Development %, Testing %, Deploy %)
Acceptance CriteriaAC count per story, writing style (Given/When/Then vs flexible), coverage patterns
Definition of DoneTeam's actual DoD items extracted from completed stories
Naming ConventionsEpic naming style (quarter-scoped, feature-based), ticket organization patterns
Team MembersPer-contributor analysis with velocity, discipline (backend/frontend/etc.), stories completed, sprint participation
Estimation BiasWhether the team tends to over- or under-estimate
Board WorkflowColumn workflow analysis showing how work items flow through states

How it works

  1. Select a board — pick your Jira project or Azure DevOps team board
  2. Choose sprint scope — analyze last 3, 5, 10, or all sprints
  3. Review the analysis — 6-page walkthrough: Instructions, Sample Epic, Sample Stories, Sample Tasks, Sample Sprint Plan, Analysis Report
  4. Save as a profile — stored in SQLite, reusable across planning sessions

Per-developer breakdown

Each team member gets individual analysis:

MetricDescription
VelocityIndividual points per sprint average
DisciplinePrimary skill area (backend, frontend, fullstack, infrastructure, etc.) — LLM-classified from actual work
Stories completedTotal stories delivered in the analysis window
Sprint participationNumber of sprints active
Delivery vs KTLOSplit between feature delivery and keeping-the-lights-on work

Analysis exports

Analysis results can be exported as HTML or Markdown reports. Both formats include all analysis sections plus a Team Members table. When an analysis profile is used during planning, the export includes a provenance note linking back to the analysis.

Analysis-Calibrated Planning

When you start a planning session, you can select a saved analysis profile. This calibrates the entire planning pipeline to match your team's real patterns.

Intake auto-fill

The analysis profile auto-fills intake questions so you don't have to answer them manually:

QuestionSource
Q6 — Team sizeReplaced with a team member multi-select picker showing each developer's velocity and discipline
Q7 — Team rolesAuto-filled from selected members' disciplines
Q8 — Sprint lengthDerived from sprint date ranges in the analysis
Q9 — VelocityCalculated from selected team members' individual per-sprint averages
Q11 — Tech stackAuto-filled from the analysis profile's tech stack (shown as suggestion, user can override)
Q12 — IntegrationsAuto-filled from the analysis profile's integrations list
Q27 — Sprint selectionFalls back to analysis sprint data when live tracker is unavailable

Team member multi-select

When an analysis profile has contributor data, Q6 (team size) becomes a multi-select picker instead of a free-text number:

  • Each member shows their velocity (pts/sprint) and discipline
  • Select specific developers for this project with Space, confirm with Enter
  • Velocity is calculated from the selected members' individual averages
  • Team roles (Q7) auto-populated from selected members' disciplines

Calibration banners

Each pipeline stage shows a calibration banner explaining what analysis data influenced the output:

StageBanner shows
Project AnalyzerSelected profile name and source board
Story WriterTarget stories/epic, AC count, points scale, DoD source
Task DecomposerTarget tasks/story, type distribution (Dev/Test/Deploy %)
Sprint PlannerSelected team members with individual velocities, total team velocity

What gets calibrated

ArtifactCalibration
EpicsLLM-reformatted to match team's naming convention (quarter-scoped, feature-based, etc.) and template sections
Stories per featureMatches team's historical average stories per epic
AC countEnforces team's median acceptance criteria count per story
AC formatRespects team's writing style (Given/When/Then or flexible)
Definition of DoneUses team's actual DoD items instead of generic checklist
Story pointsIncludes confidence scoring and references to similar stories from the analysis
Tasks per storyMatches team's average task count
Task type distributionMatches team's Development/Testing/Deploy percentages

Epic review

Before the feature generator runs, an epic review page lets you review and edit the project epic. When an analysis profile is active, the epic is LLM-reformatted to match your team's style:

  • Quarter-scoped naming when the team uses that convention (e.g., "Q2 2026 — Customer Portal")
  • Template sections matching the team's epic structure
  • Sync to Jira or Azure DevOps directly from the review page