sprint-autopilot

name	sprint-autopilot
description	Work on a sprint issue with dynamic persona switching. Stages: issue analysis, branch setup via start_work, code research, implementation (in chat), MR creation, optional deployment check. Use when user says "autopilot", "work on sprint issue", or "work on AAP-XXXXX". Use when this capability is needed.

Sprint Autopilot

Orchestrates work on a single sprint issue. Different stages load different personas. Implementation happens in Cursor chat; autopilot prepares context.

Inputs

Input	Type	Default	Purpose
issue_key	string	required	Jira issue key (e.g., AAP-12345)
repo_path	string	"."	Path to repository
needs_deployment_check	bool	false	Deploy to ephemeral after MR
auto_stash	bool	true	Stash uncommitted changes
skip_clarity_check	bool	false	Skip issue clarity check

Workflow

Stage 1: Issue Analysis (developer)

• persona_load(persona="developer")
• git_status(repo=repo_path) — Check for uncommitted changes, rebase/merge, protected branch
• If unsafe (rebase/merge/protected): abort with reason
• If uncommitted and auto_stash: git_stash(repo=repo_path, action="push", message="Auto-stash before {issue_key}")
• jira_view_issue(issue_key=issue_key) — Fetch issue details

Stage 2: Clarity Check (unless skip_clarity_check)

Parse issue for: acceptance criteria, description length (>200), technical terms (API, endpoint, database, etc.)

• If needs_clarification: jira_add_comment(issue_key=issue_key, comment="I'm reviewing this issue... Could you provide: [missing items]?")
• If unclear: mark waiting, skip remaining steps

Stage 3: Branch Setup (developer)

• skill_run(skill_name="start_work", inputs='{"issue_key": "' + issue_key + '", "auto_stash": false}')
• persona_load(persona="developer") — Restore after start_work
• Extract branch_name from result

Stage 4: Code Research (developer)

• code_search(query=issue_summary_or_key, limit=10) — Find relevant patterns
• knowledge_query(project="", section="patterns") — Project patterns
• Build context: issue details + relevant code + project patterns

Stage 5: Implementation

• Log to state/sprint_timeline: ready_for_implementation
• Note: Actual coding happens in Cursor chat; autopilot prepares context only

Stage 6: MR Creation (when changes exist)

• git_status(repo=repo_path) — Check for changes
• If has_changes: skill_run(skill_name="create_mr", inputs='{"issue_key": "' + issue_key + '", "draft": true}')
• persona_load(persona="developer") — Restore
• Extract mr_url, mr_id from result

Stage 7: Deployment Check (if needs_deployment_check)

• persona_load(persona="devops")
• skill_run(skill_name="test_mr_ephemeral", inputs='{"mr_id": "' + mr_id + '"}')
• persona_load(persona="developer") — Switch back

Stage 8: Finalize (developer)

• jira_add_comment(issue_key=issue_key, comment="Merge request ready for review: {mr_url}")
• Log to state/sprint_timeline: mr_created

Output Format

## Sprint Autopilot Summary for AAP-12345

**Status:** MR Created
**MR URL:** https://gitlab.com/.../merge_requests/1234
**Branch:** aap-12345-fix-auth

OR

**Status:** Waiting for clarification
**Reason:** Missing: acceptance criteria, technical details

OR

**Status:** Ready for implementation
Context prepared. Work can continue in dedicated chat.

Key MCP Tools

• persona_load, git_status, git_stash, jira_view_issue, jira_add_comment, skill_run, code_search, knowledge_query, memory_append

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