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This skill orchestrates autonomous sprint execution by coordinating subagents to implement GitHub issues serially. It manages the full lifecycle: generating implementation plans via Gemini CLI, delegating implementation to subagents, reviewing PRs with Codex MCP, merging approved code, and running post-merge integration. Use this skill when asked to "run a sprint", "execute sprint issues", "implement issues autonomously", or "manage sprint workflow".

$ Installer

git clone https://github.com/bodangren/git-workflow /tmp/git-workflow && cp -r /tmp/git-workflow/skills/sprint-manager ~/.claude/skills/git-workflow

// tip: Run this command in your terminal to install the skill


name: sprint-manager description: This skill orchestrates autonomous sprint execution by coordinating subagents to implement GitHub issues serially. It manages the full lifecycle: generating implementation plans via Gemini CLI, delegating implementation to subagents, reviewing PRs with Codex MCP, merging approved code, and running post-merge integration. Use this skill when asked to "run a sprint", "execute sprint issues", "implement issues autonomously", or "manage sprint workflow".

Sprint Manager

Purpose

To autonomously execute a sprint by coordinating the implementation of GitHub issues through a structured workflow that leverages subagents for isolated work and maintains a clean context window for sprint-level coordination.

When to Use

Use this skill in the following situations:

  • Starting work on a set of sprint issues from a GitHub milestone
  • Implementing multiple issues autonomously with minimal user intervention
  • Coordinating a development workflow that requires code review and integration
  • Managing serial execution of dependent or independent issues

Prerequisites

  • GitHub repository with issues assigned to a milestone
  • Git working directory is clean (no uncommitted changes)
  • gh CLI tool installed and authenticated
  • gemini CLI tool installed and authenticated (optional, for plan generation)
  • Codex MCP available for PR review
  • Project has issue-executor and change-integrator skills (or equivalent workflow)

Architecture

The sprint manager operates as a coordinator that delegates work to subagents:

Sprint Manager (main context)
│
├── For each issue:
│   ├── 1. Generate implementation plan (Gemini CLI or manual)
│   ├── 2. Create feature branch
│   ├── 3. Launch implementer subagent → creates PR
│   ├── 4. Review PR (Codex MCP)
│   ├── 5. Fix issues if needed (another subagent)
│   ├── 6. Merge on approval
│   └── 7. Launch integrator subagent → cleanup & retrospective
│
└── Report sprint summary

Core Workflow

Phase 1: Sprint Setup

  1. Identify sprint issues by querying the GitHub milestone:

    gh issue list --milestone "Sprint X" --state open --json number,title,labels
    
  2. Prioritize issues based on labels (P0 > P1 > P2) and dependencies

  3. Track progress using the TodoWrite tool with all sprint issues

Phase 2: Issue Execution Loop

For each issue in priority order:

Step 1: Generate Implementation Plan

Option A - Use issue-executor skill (if Gemini available):

bash scripts/work-on-issue.sh <issue-number>

Option B - Manual plan generation:

  1. Fetch issue details: gh issue view <number> --json title,body
  2. Read relevant specs from docs/specs/ or docs/changes/
  3. Call Gemini CLI with context to generate a step-by-step plan
  4. Create feature branch following convention: feat/<number>-<kebab-title>

Step 2: Delegate Implementation to Subagent

Launch a Task subagent with a comprehensive prompt including:

  • Issue number and acceptance criteria
  • Implementation plan from Step 1
  • Project conventions (from CLAUDE.md)
  • File paths and schema context
  • Expected deliverables (PR URL, test results, files created)
  • Fallback instructions if tools fail

Select appropriate subagent type based on the issue:

  • backend-architect - API routes, database schemas, backend logic
  • frontend-developer - React components, UI, client-side code
  • general-purpose - Mixed or unclear scope

Example prompt structure (see references/implementer-prompt-template.md):

## Task: Implement GitHub Issue #<number> - <title>

You are working on branch `<branch-name>` in `<working-directory>`.

### Issue Summary
<brief description>

### Implementation Plan
<step-by-step plan from Gemini or manual>

### Project Conventions
<key conventions from CLAUDE.md>

### Your Deliverables
1. Implement the code
2. Run lint and tests
3. Commit with conventional commit message
4. Push and create PR

### Report Back
<what to return: PR URL, test results, issues encountered>

Step 3: Review PR with Codex MCP

After subagent returns with PR URL:

mcp__codex__codex with prompt:
"Review PR #<number>: <title>
URL: <pr-url>

The PR implements: <summary>

Focus your review on: <relevant concerns>

Say APPROVED if ready to merge, or list issues with severity."

Step 4: Handle Review Feedback

If Codex finds issues:

  1. Launch another subagent to fix the issues
  2. Provide specific fix instructions from Codex feedback
  3. Re-review after fixes are pushed

If Codex approves:

  • Proceed to merge

Step 5: Merge PR

gh pr merge <number> --squash --auto

Wait for CI to pass, then verify merge:

gh pr view <number> --json state

Step 6: Post-Merge Integration

Launch integrator subagent (see references/integrator-prompt-template.md):

  1. Switch to main and pull latest
  2. Delete feature branch (local and remote)
  3. Update retrospective with learnings
  4. Close issue if not auto-closed
  5. Report completion status

Phase 3: Sprint Completion

After all issues are processed:

  1. Update TodoWrite to mark all issues complete
  2. Summarize sprint results:
    • Issues completed
    • PRs merged
    • Key learnings
    • Any blockers encountered
  3. Report to user

Error Handling

Gemini CLI Fails

If the Gemini CLI fails during plan generation:

  • Fall back to manual plan creation
  • Read issue details directly via gh issue view
  • Check relevant specs in docs/specs/ or docs/changes/
  • Construct implementation plan based on acceptance criteria

Subagent Fails

If an implementer subagent fails:

  • Review the error reported
  • Launch a new subagent with adjusted instructions
  • Consider breaking the task into smaller pieces
  • Flag for user intervention if repeated failures

Codex Review Times Out

If Codex MCP doesn't respond:

  • Retry the review request
  • Fall back to basic automated checks (lint, tests)
  • Flag PR for user manual review

PR Merge Conflicts

If merge fails due to conflicts:

  • Rebase the branch on main
  • Launch subagent to resolve conflicts
  • Re-run tests and review

Prompt Templates

See the references/ directory for detailed prompt templates:

  • references/implementer-prompt-template.md - Template for implementation subagents
  • references/integrator-prompt-template.md - Template for post-merge integration subagents
  • references/review-prompt-template.md - Template for Codex PR reviews

Best Practices

Context Management

  • Keep sprint-level state in the main context (issue tracking, PR URLs, blockers)
  • Delegate all implementation details to subagents
  • Each subagent gets a fresh context - include all needed info in the prompt

Prompt Crafting

  • Be specific about file paths and existing code context
  • Include project conventions explicitly (subagents don't read CLAUDE.md)
  • Specify exact deliverables and report format
  • Provide fallback instructions for common failure modes

Serial vs Parallel

  • Default to serial execution for safety and easier debugging
  • Only parallelize truly independent issues with explicit user approval
  • Never parallelize issues with shared file dependencies

User Communication

  • Report progress after each issue completes
  • Flag blockers immediately rather than retrying indefinitely
  • Provide sprint summary at the end

Notes

  • This skill is designed for serial execution to maintain context clarity
  • Each issue gets its own subagent context, keeping the main context clean
  • The workflow integrates with existing issue-executor and change-integrator skills
  • Codex MCP provides automated code review without user intervention
  • Retrospective updates capture learnings for future sprints