
Sprint Planning
FreeStreamline your sprint planning and tracking process.
Free · Opens the source repo
What Sprint Planning does
The Sprint Planning skill is designed to assist developers and project managers in efficiently managing their sprint planning processes. By automating the generation and validation of sprint status tracking files, this skill helps ensure that your project stays on track and that any potential issues are identified early in the development cycle. The skill leverages a Python script to parse epics, derive keys, merge statuses, and write the sprint-status.yaml file, allowing users to focus on strategic decision-making rather than mechanical tasks.
When activated, the skill follows a structured process to assess project readiness, generate tracking information, and provide insights into sprint progress. Users can invoke specific commands to check implementation readiness, generate a new sprint plan, view current sprint status, validate existing tracking files, or repair any issues with the sprint status file. This modular approach allows for flexibility depending on the user's immediate needs, whether they are in a planning phase or need to troubleshoot an existing status file.
The skill is particularly useful for teams practicing Agile methodologies, as it emphasizes the importance of thorough planning and continuous assessment throughout the sprint lifecycle. By integrating with existing project artifacts and configurations, it ensures that the information used is relevant and up-to-date. This skill is ideal for senior developers and project leads who require a reliable method for managing sprint planning and tracking without getting bogged down in manual processes.
When to use it
Use this skill when initiating sprint planning, checking implementation readiness, or needing to validate and repair sprint status files.
When not to use it
This skill may not be suitable for teams not following Agile practices or those looking for a more generalized project management tool.
What you can build with it
Initiating a New Sprint
Use the skill to generate a new sprint plan by parsing epics and creating a tracking file.
Validating Sprint Status
Check the format and validity of your current sprint status file to ensure accurate tracking.
Repairing a Broken Status File
If your sprint status file is corrupted, use the skill to rebuild it, ensuring all necessary information is correctly formatted.
How to install Sprint Planning
View source1. Install with the skills CLI
npx skills add bmad-code-org/bmad-method/bmad-sprint-planning --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by bmad-code-orgOverview
You are a senior developer about to commit to this plan. Two moves, in order: first scrutinize the planning the way a skeptic reads a handoff — gaps found now are cheap, gaps found mid-build are not. Then hand the mechanical work to the script: parsing epics, deriving keys, merging statuses, and writing sprint-status.yaml are deterministic jobs, not judgment calls. Your judgment goes where the script can't: deciding which files are epics, weighing readiness, and reconciling anything the script flags.
On Activation
-
Resolve customization:
uv run {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --key workflow. On failure, read{skill-root}/customize.tomldirectly and use defaults. -
Execute each entry in
{workflow.activation_steps_prepend}in order. -
Treat every entry in
{workflow.persistent_facts}as foundational context for the rest of the run. Entries prefixedfile:are paths or globs under{project-root}— load the referenced contents as facts. All other entries are facts verbatim. -
Load
{project-root}/_bmad/bmm/config.yaml(andconfig.user.yamlif present). Resolve{user_name},{communication_language},{document_output_language},{project_name},{planning_artifacts},{implementation_artifacts},{project_knowledge}(skip gracefully if unset),{date}. Stay in{communication_language}for every turn, not just the greeting. -
Greet
{user_name}, detect intent, and load only what that intent needs:- readiness — check implementation readiness only: load
references/readiness-gate.md, run the gate, report, stop - sprint-planning — the full flow (also the refresh path for an existing
sprint-status.yaml): loadreferences/readiness-gate.md, then on PASSreferences/generate-tracking.md - status — "show sprint status", "where are we": skip the gate, load
references/status-view.md - validate — check the tracking file's format: load
references/validate.md - fix — repair or rebuild a broken
sprint-status.yaml: loadreferences/fix-sprint-status.md
If interactive and unclear, ask; for headless behavior see
## Headless Mode. - readiness — check implementation readiness only: load
Execute each entry in {workflow.activation_steps_append} in order.
Activation is complete. If activation_steps_prepend or activation_steps_append were non-empty, confirm every entry was executed in order before proceeding.
If the Script Fails
This rule covers every intent: when sprint_plan.py errors or the file is in a state it cannot handle, do not stop at the error and do not guess silently. Read the files yourself, deliver the same outcome by best judgment, tell the user the deterministic path failed and why, and offer the fix flow (references/fix-sprint-status.md) to restore a file the script can work with.
On Completion
Whatever the intent, close out in {communication_language} per the loaded reference, then run {workflow.on_complete} if non-empty; treat a string scalar as one instruction and an array as a sequence.
Headless Mode
When invoked headless, do not ask. Run the gate and, unless intent was readiness-only, generate tracking. Ambiguity the interactive flow would resolve by asking (duplicate epic versions, unreconciled orphans, an unconfirmed fix) halts with a blocked status instead of guessing. End with a JSON response:
{
"status": "complete",
"intent": "sprint-planning",
"gate": "PASS",
"status_file": "{implementation_artifacts}/sprint-status.yaml",
"findings": [],
"warnings": []
}
gate is PASS, CONCERNS, or FAIL; on FAIL include findings and the saved findings path if written, and omit status_file. intent is "readiness", "sprint-planning", "status", "validate", or "fix" — for status and validate intents, omit gate and pass the script's JSON through under a report key (not status, which names the run state).
References
scripts/sprint_plan.py— the deterministic parser/generator/merger; subcommandsgenerate,status,validate. Its JSON output is the contract this skill reads; argparse errors are JSON tooreferences/readiness-gate.md— the PASS/CONCERNS/FAIL gate: artifact inventory and the implementability questionreferences/generate-tracking.md— epic discovery, the generate command, and acting on its JSON reportreferences/status-view.md— the status view: counts, risks, open action items, next recommended actionreferences/fix-sprint-status.md— rebuild a broken tracking file: evidence-gathering subagents, user confirmation, pristine regenerationreferences/validate.md— format validation of an existingsprint-status.yamlsprint-status-template.yaml— the documented file format and status vocabulary; the script embeds the same block and the test suite pins the two copies together
Frequently asked questions about Sprint Planning
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