About scrum-conductor
Scrum Conductor is a skill for coordinating Scrum ceremonies and delivery planning. It turns git and PR activity into factual updates and supports ticket quality, sprint capacity, backlog refinement, blocker detection, and risk tracking.
Key features
- 01Summarize git and PR activity for standups
- 02Create tickets with acceptance criteria
- 03Calculate sprint capacity from velocity and availability
- 04Cluster and prune backlog items
- 05Detect blockers across PRs and dependencies
- 06Track risks and retrospective actions
Use cases
- 01Prepare fact-based daily standup updates
- 02Plan sprint scope using team capacity
- 03Refine and deduplicate issue backlogs
- 04Identify delivery blockers and track follow-up actions
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ oakoss/ agent-skills --skill scrum-conductorAfter installing, type/scrum-conductorin Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
references/agile-agents.mddaily-rituals.mdticket-engineering.mdvelocity-risk.mdDetails
From the project READMEScrum Conductor
Overview
Facilitates AI-enhanced Scrum orchestration with automated ticket management and high-velocity sprint coordination. Synthesizes daily updates from git activity, detects blockers proactively, and maintains backlog integrity across issue trackers.
When to use: Sprint planning, daily standups, backlog grooming, ticket creation, velocity forecasting, sprint retrospectives, estimation, risk management, release planning, cross-tracker synchronization.
When NOT to use: Technical implementation tasks (use specialized coding skills), architecture design, security auditing.
Quick Reference
| Pattern | Approach | Key Points |
|---|---|---|
| Fact-first standups | Auto-generate from git logs and PRs | Never ask humans for data in commit history |
| Ticket engineering | Machine-readable DoD with acceptance criteria | Binary true/false criteria, implementation pointers |
| Sprint planning | Capacity calculation with focus factor and velocity | Budget = avg velocity (last 3 sprints) adjusted for absences |
| Estimation | Planning Poker with Fibonacci scale, T-shirt sizing for roadmap | Reference stories anchor the scale, re-calibrate quarterly |
| Capacity forecasting | Historical cycle time and lead time | Factor holidays, context debt, and bottlenecks |
| Backlog grooming | AI clustering and deduplication | Flag tickets older than 2 sprints for archive |
| Backlog refinement | 1-2 sessions per sprint, Definition of Ready checklist | Stories must meet DoR before entering sprint planning |
| Blocker detection | Scan PRs, assignments, and dependencies | Flag stale PRs, OOO assignees, breaking deps |
| Parking lot | Move deep-dives out of standups | Standups focus on status and blockers only |
| Sprint retrospective | Start/Stop/Continue with action item tracking | Track retro action completion rate across sprints |
| Risk management | Dependency mapping, risk register (probability x impact) | Address risk scores 6+ immediately, monitor 3-5 |
| Release planning | Multi-sprint roadmap with confidence levels | Feature flags decouple deployment from release |
| Escalation tiers | Tier 1 autonomous, Tier 2 clarification, Tier 3 pairing | Match response to complexity |
| Priority frameworks | MoSCoW, value vs effort matrix, WSJF | WSJF favors small high-value items |
Conductor Protocol
- Ceremony Initialization: Identify the current sprint phase (Planning, Daily, Review, Retro)
- Telemetry Sync: Pull recent activity from git commits, PRs, and communication channels
- Fact Synthesis: Generate factual summaries before ceremonies begin
- Verification: Confirm all action items are converted into tracked tickets with clear owners and DoD
Common Mistakes
| Mistake | Correct Pattern |
|---|---|
| Asking developers for status updates available in commit logs | Auto-generate fact summaries from PRs and merges before standups |
| Creating tickets without a machine-readable Definition of Done | Every ticket needs explicit acceptance criteria and technical pointers |
| Guessing sprint velocity without historical data | Use cycle time, holidays, and context debt to forecast capacity |
| Letting standups run beyond 15 minutes with deep-dive discussions | Move deep-dives to a parking lot session; standups focus on blockers |
| Allowing the backlog to grow to 200+ items without pruning | Auto-flag tickets older than 2 sprints for archive or refactor |
| Using AI to replace human conversation | Use AI to prepare for the conversation, not substitute it |
| Ignoring team sentiment and morale signals | High velocity with low morale is a leading indicator of burnout |
| No Definition of Done agreed by the team | Establish a team-wide DoD checklist applied to every story |
| Skipping retrospectives when the sprint "went fine" | Every sprint has improvement opportunities; consistency builds the habit |
| Sprint planning without capacity calculation | Calculate capacity: members x available days x focus factor |
| Stories entering sprint without acceptance criteria | Enforce Definition of Ready before stories enter a sprint |
| Estimating stories individually instead of as a team | Use Planning Poker so the full team contributes perspective |
| Slicing stories horizontally by layer | Slice vertically through all layers so each ticket delivers working functionality |
| No dependency mapping between sprint stories | Map dependencies explicitly and identify the critical path |
| Retro action items with no owner or due date | Every action item needs an owner, a due date, and follow-up tracking |
Delegation
- Synthesize daily standup summaries from git activity and PRs: Use
Taskagent to pull commit logs and generate fact-based updates - Cluster and deduplicate backlog tickets across issue trackers: Use
Exploreagent to scan GitHub Issues, Jira, and Linear for similar or conflicting items - Plan sprint capacity and risk assessment using historical velocity: Use
Planagent to model delivery probability and identify at-risk items
References
- Automated daily rituals, fact-checking workflows, blocker detection, sprint planning, retrospectives, and refinement
- Ticket engineering standards, user story templates, estimation techniques, and priority frameworks
- Predictive velocity, sprint metrics, risk management, distributed teams, and release planning
- Multi-agent task handoffs, escalation tiers, AI retrospectives, blocker detection, and human escalation guardrails