4.7 KiB
name, description
| name | description |
|---|---|
| sprint-planner | Use this skill to plan a new sprint. It uses the Gemini CLI to intelligently decompose approved specs into atomic GitHub issues for the development team. Triggers include "plan sprint", "create sprint", or "start new sprint". |
Sprint Planner Skill
Purpose
To plan and initialize a new sprint by intelligently decomposing approved specifications into a comprehensive set of atomic GitHub issues. This skill bridges the gap between high-level specs and executable work items by using the Gemini CLI to analyze the spec's content and generate a thoughtful task breakdown. It then automates the creation of these tasks as GitHub issues within a new sprint milestone.
When to Use
Use this skill in the following situations:
- Starting a new sprint or development cycle.
- Converting an approved spec into actionable GitHub issues.
- When you want an AI-assisted breakdown of an epic into atomic implementation tasks.
Prerequisites
- Project board configured with an "Approved Backlog" status column.
- Approved spec files exist in the
docs/specs/directory. - An Epic issue exists on GitHub that links to the spec file in its body.
ghCLI tool installed and authenticated.jqtool installed for JSON parsing.geminiCLI tool installed and authenticated.
Workflow
Step 1: Review Project Board
Check the project board for approved specs (represented as Epics) ready to be planned.
Step 2: Discuss Sprint Scope with User
Engage the user to determine which epic(s) from the "Approved Backlog" to include in the sprint.
Step 3: Define Sprint Metadata
Work with the user to establish the sprint name (e.g., "Sprint 4").
Step 4: Run the Helper Script
Execute the sprint planning script to automate GitHub issue creation:
bash scripts/create-sprint-issues.sh
Step 5: Understand What the Script Does
The helper script automates these steps:
- Queries Project Board: Fetches all items from the "Approved Backlog" and prompts you to select an Epic to plan.
- Extracts Spec File: Parses the selected Epic's body to find the associated spec file path.
- Creates Milestone: Prompts you for a sprint name and creates the corresponding GitHub milestone.
- Decomposes Spec with AI: Instead of relying on a rigid format, the script sends the full content of the spec file and the parent Epic to the Gemini CLI. It asks the AI to generate a list of atomic, actionable tasks based on its understanding of the document.
- Creates GitHub Issues: The script parses the structured task list from Gemini's response and creates a GitHub issue for each task. Each issue is automatically titled, assigned to the new milestone, and includes a description and references to the parent Epic and spec file.
Step 6: Verify Issue Creation
After the script completes, review the newly created issues in your milestone.
gh issue list --milestone "Your Sprint Name"
Step 7: Review Created Issues with User
Walk through the AI-generated issues with your team. The generated tasks provide a strong baseline, but you should review them to confirm completeness, adjust priorities, and make any necessary refinements.
Error Handling
jq or Gemini Not Installed
Symptom: Script reports that jq or gemini command is not found.
Solution: Install the required tool and ensure it's in your system's PATH.
No Approved Epics Found
Symptom: Script reports no epics in the approved backlog. Solution: Ensure your Epics are in the correct status column on your project board.
Epic Body Missing Spec Reference
Symptom: Script cannot find a spec file path in the Epic's body.
Solution: Edit the Epic's issue body on GitHub to include a valid path to a spec file (e.g., docs/specs/my-feature.md).
Gemini CLI Issues
Symptom: The script fails during the task decomposition step with an error from the gemini command.
Solution:
- Ensure the
geminiCLI is installed and authenticated (gemini auth). - Check for API outages or network issues.
- The quality of the task breakdown depends on a functional Gemini CLI.
Notes
- Intelligent Decomposition: The skill no longer relies on a rigid task format in spec files. Gemini reads and understands the document to create tasks.
- LLM guides strategy, script executes: You decide which spec to plan; the script uses AI to handle the tedious decomposition and issue creation.
- One epic per run: Run the script once for each Epic you want to plan for the sprint.
- Traceability is built-in: Each created task issue automatically references the parent Epic and the source spec file.
- Manual refinement is expected: The AI-generated task list is a starting point. Review and adjust it with your team.