AILANG Sprint Executor

AILANG Sprint Executor

Execute an approved sprint plan with continuous progress tracking, testing, and documentation updates.

Quick Start

Most common usage:

# User says: "Execute the sprint plan in design_docs/20251019/M-S1.md"
# This skill will:
# 1. Validate prerequisites (tests pass, linting clean)
# 2. Create TodoWrite tasks for all milestones
# 3. Execute each milestone with test-driven development
# 4. Run checkpoint after each milestone (tests + lint)
# 5. Update CHANGELOG and sprint plan progressively
# 6. Pause after each milestone for user review

When to Use This Skill

Invoke this skill when:

• User says "execute sprint", "start sprint", "begin implementation"
• User has an approved sprint plan ready to implement
• User wants guided execution with built-in quality checks
• User needs progress tracking and pause points

Coordinator Integration

When invoked by the AILANG Coordinator (detected by GitHub issue reference in the prompt), you MUST output these markers at the end of your response:

IMPLEMENTATION_COMPLETE: true
BRANCH_NAME: coordinator/task-XXXX
FILES_CREATED: file1.go, file2.go
FILES_MODIFIED: file3.go, file4.go

Why? The coordinator uses these markers to:

1. Track implementation completion
2. Post updates to GitHub issues
3. Trigger the merge approval workflow

Example completion:

## Implementation Complete

All milestones have been completed and tests pass.

**IMPLEMENTATION_COMPLETE**: true
**BRANCH_NAME**: `coordinator/task-abc123`
**FILES_CREATED**: `internal/new_file.go`, `internal/new_test.go`
**FILES_MODIFIED**: `internal/existing.go`

Core Principles

1. Test-Driven: All code must pass tests before moving to next milestone
2. Lint-Clean: All code must pass linting before moving to next milestone
3. Document as You Go: Update CHANGELOG.md and sprint plan progressively
4. Pause for Breath: Stop at natural breakpoints for review and approval
5. Track Everything: Use TodoWrite to maintain visible progress
6. DX-First: Improve AILANG development experience as we go - make it easier next time

Multi-Session Continuity (NEW)

Sprint execution can now span multiple Claude Code sessions!

Based on Anthropic's long-running agent patterns, sprint-executor implements the "Coding Agent" pattern:

• Session Startup Routine: Every session starts with session_start.sh

  • Checks working directory
  • Reads JSON progress file (.ailang/state/sprints/sprint_<id>.json)
  • Reviews recent git commits
  • Validates tests pass
  • Prints "Here's where we left off" summary

• Structured Progress Tracking: JSON file tracks state

  • Features with passes: true/false/null (follows "constrained modification" pattern)
  • Velocity metrics updated automatically
  • Clear checkpoint messages
  • Session timestamps

• Pause and Resume: Work can be interrupted at any time

  • Status saved to JSON: not_started, in_progress, paused, completed
  • Next session picks up exactly where you left off
  • No loss of context or progress

For JSON schema details, see resources/json_progress_schema.md

Available Scripts

scripts/session_start.sh <sprint_id> NEW

Resume sprint execution across multiple sessions.

When to use: ALWAYS at the start of EVERY session continuing a sprint.

What it does:

1. Syncs GitHub issues via ailang messages import-github
2. Loads sprint JSON progress file
3. Shows linked GitHub issues with titles from local messages
4. Displays feature progress summary
5. Shows velocity metrics
6. Runs tests to verify clean state
7. Prints "Here's where we left off" summary

scripts/validate_prerequisites.sh

Validate prerequisites before starting sprint execution.

What it checks:

1. Syncs GitHub issues via ailang messages import-github
2. Working directory status (clean/uncommitted changes)
3. Current branch (dev or main)
4. Test suite passes
5. Linting passes
6. Shows unread messages (potential issues/feedback)

scripts/validate_sprint_json.sh <sprint_id> NEW

REQUIRED before starting any sprint. Validates that sprint JSON has real milestones (not placeholders).

What it checks:

• No placeholder milestone IDs (MILESTONE_ID)
• No placeholder acceptance criteria (Criterion 1/2)
• At least 2 milestones defined
• All milestones have custom values (not defaults)
• Dependencies reference valid milestone IDs

Exit codes:

• 0 - Valid JSON, ready for execution
• 1 - Invalid JSON or placeholders detected (sprint-planner must fix)

scripts/milestone_checkpoint.sh <milestone_name> [sprint_id]

Run checkpoint after completing a milestone.

CRITICAL: Tests passing ≠ Feature working! This script verifies with REAL DATA.

What it does:

1. Runs make test and make lint
2. Shows git diff of changed files
3. Checks file sizes (AI-friendly codebase guidelines)
4. Runs milestone-specific verification (database queries, API calls, etc.)
5. Shows JSON update reminder with current milestone statuses

Sprint-specific verification (e.g., M-TASK-HIERARCHY):

• M1: Checks observatory_sync.go exists, tasks in DB with non-empty IDs
• M2: Checks OTEL_RESOURCE_ATTRIBUTES in executor, spans with task attributes
• M3: Checks spans have task_id linked
• M4: Checks task aggregates (span_count, tokens) are populated
• M5: Checks hierarchy API returns data for existing tasks
• M6: Checks TaskHierarchy component imported AND connected in UI
• M7: Checks backfill command exists and responds to --help

Example:

# Verify M1 (should pass if entity sync works)
.claude/skills/sprint-executor/scripts/milestone_checkpoint.sh M1 M-TASK-HIERARCHY

# Verify M2 (will fail if OTEL attributes not propagated)
.claude/skills/sprint-executor/scripts/milestone_checkpoint.sh M2 M-TASK-HIERARCHY

Exit codes:

• 0 - Checkpoint passed (all verifications succeeded)
• 1 - Checkpoint FAILED (DO NOT mark milestone complete)

scripts/acceptance_test.sh <milestone_id> <test_type> NEW

Run end-to-end acceptance tests (parser, builtin, examples, REPL, e2e).

scripts/finalize_sprint.sh <sprint_id> [version] NEW

Finalize a completed sprint by moving design docs and updating status.

What it does:

• Moves design doc from planned/ to implemented/<version>/
• Moves sprint plan markdown to implemented/<version>/
• Updates design doc status to "IMPLEMENTED"
• Updates sprint JSON status to "completed"
• Updates file paths in sprint JSON

When to use: After all milestones pass and sprint is complete.

Example:

.claude/skills/sprint-executor/scripts/finalize_sprint.sh M-BUG-RECORD-UPDATE-INFERENCE v0_4_9

Execution Flow

Phase 0: Session Resumption (for continuing sprints)

If this is NOT the first session for this sprint:

# ALWAYS run session_start.sh first!
.claude/skills/sprint-executor/scripts/session_start.sh <sprint-id>

This prints "Here's where we left off" summary. Then skip to Phase 2 to continue with the next milestone.

Phase 1: Initialize Sprint (first session only)

1. Validate Sprint JSON - Run validate_sprint_json.sh <sprint-id> REQUIRED FIRST
   • If validation fails, STOP and notify user that sprint-planner must fix the JSON
   • Do NOT proceed with placeholder milestones
2. Read Sprint Plan - Parse markdown + load JSON progress file (.ailang/state/sprints/sprint_<id>.json)
3. Validate Prerequisites - Run validate_prerequisites.sh (tests, linting, git status)
4. Create Todo List - Use TodoWrite to track all milestones
5. Initial Status Update - Mark sprint as "🔄 In Progress"
6. Initial DX Review - Consider tools/helpers that would make sprint easier (see resources/dx_improvement_patterns.md)

Phase 2: Execute Milestones

For each milestone:

1. Pre-Implementation - Mark milestone as in_progress in TodoWrite
2. Implement - Write code with DX awareness (helper functions, debug flags, better errors)
3. Write Tests - TDD recommended for complex logic, comprehensive coverage required
4. Verify Quality - Run milestone_checkpoint.sh <milestone-name> (tests + lint must pass)
5. Update Documentation:
   • CHANGELOG.md (what, LOC, key decisions)
   • Example files (REQUIRED for new features)
   • Sprint plan markdown (mark milestone as ✅)
6. Update Sprint JSON ⚠️ CRITICAL - The checkpoint script reminds you!
   • Update passes: true/false in .ailang/state/sprints/sprint_<id>.json
   • Set completed: "<ISO timestamp>"
   • Add notes: "<summary of what was done>"
7. DX Reflection - Identify and implement quick wins (<15 min), defer larger improvements
8. Pause for Breath - Show progress, ask user if ready to continue

Quick tips:

• Use parser test helpers from internal/parser/test_helpers.go
• Use DEBUG_PARSER=1 for token flow tracing
• Use make doc PKG=<package> for API discovery
• See resources/parser_patterns.md for parser/pattern matching
• See resources/codegen_patterns.md for Go code generation (builtins, expressions)
• See resources/api_patterns.md for common API patterns
• See resources/dx_improvement_patterns.md for DX opportunities

Phase 3: Finalize Sprint

1. Final Testing - Run make test, make lint, make test-coverage-badge
2. Documentation Review - Verify CHANGELOG.md, example files, sprint plan complete
3. Final Commit - Git commit with sprint summary (milestones, LOC, velocity)
4. Move Design Docs - Run finalize_sprint.sh <sprint-id> [version] to:
   • Move design docs from planned/ to implemented/<version>/
   • Update design doc status to IMPLEMENTED
   • Update sprint JSON status to "completed"
   • Update file paths in sprint JSON
5. Summary Report - Compare planned vs actual (LOC, time, velocity)
6. DX Impact Summary - Document improvements made during sprint

Key Features

Continuous Testing

• Run make test after every file change
• Never proceed if tests fail
• Track test count increase

Continuous Linting

• Run make lint after implementation
• Fix linting issues immediately
• Use make fmt for formatting

Progress Tracking

• TodoWrite shows real-time progress
• Sprint plan updated at each milestone
• CHANGELOG.md grows incrementally
• JSON file tracks structured state (NEW)
• Git commits create audit trail

GitHub Issue Integration (NEW)

Uses ailang messages for GitHub sync and issue tracking!

Automatic sync:

• session_start.sh and validate_prerequisites.sh run ailang messages import-github first
• Linked issues shown with titles from local message database

If github_issues is set in sprint JSON:

• validate_sprint_json.sh shows linked issues
• session_start.sh displays issue titles from messages
• milestone_checkpoint.sh reminds you to include Refs #... in commits
• finalize_sprint.sh suggests commit message with issue references

Commit message format:

# During development - use "refs" to LINK without closing
git commit -m "Complete M1: Parser foundation, refs #17"

# Final sprint commit - use "Fixes" to AUTO-CLOSE issues on merge
git commit -m "Finalize sprint M-BUG-FIX

Fixes #17
Fixes #42"

Important: "refs" vs "Fixes"

• refs #17 - Links commit to issue (NO auto-close)
• Fixes #17, Closes #17, Resolves #17 - AUTO-CLOSES issue when merged

Workflow:

1. Sprint JSON has github_issues: [17, 42] (set by sprint-planner, deduplicated)
2. During development: Use refs #17 to link commits without closing
3. Final commit: Use Fixes #17 to auto-close issues on merge
4. No duplicates: ailang messages import-github checks existing issues before importing

Pause Points

• After each milestone completion
• When tests or linting fail (fix before continuing)
• When user requests "pause"
• When encountering unexpected issues

Error Handling

• If tests fail: Show output, ask how to fix, don't proceed
• If linting fails: Show output, ask how to fix, don't proceed
• If implementation unclear: Ask for clarification, don't guess
• If milestone takes much longer than estimated: Pause and reassess

Resources

Multi-Session State

• JSON Schema: resources/json_progress_schema.md - Sprint progress format
• Session Startup: Use session_start.sh ALWAYS for continuing sprints

Development Tools

• Parser & Patterns: resources/parser_patterns.md - Parser development + pattern matching pipeline
• Codegen Patterns: resources/codegen_patterns.md - Go code generation for new features/builtins
• API Patterns: resources/api_patterns.md - Common constructor signatures and API gotchas
• Developer Tools: resources/developer_tools.md - Make targets, ailang commands, workflows
• DX Improvements: resources/dx_improvement_patterns.md - Identifying and implementing DX wins
• DX Quick Reference: resources/dx_quick_reference.md - ROI calculator, decision matrix
• Milestone Checklist: resources/milestone_checklist.md - Step-by-step per milestone

External Documentation

• Parser Guide: docs/guides/parser_development.md
• Website: https://ailang.sunholo.com/

Progressive Disclosure

This skill loads information progressively:

1. Always loaded: This SKILL.md file (YAML frontmatter + execution workflow) - ~250 lines
2. Execute as needed: Scripts in scripts/ directory (validation, checkpoints, testing)
3. Load on demand: Resources in resources/ directory (detailed guides, patterns, references)

Prerequisites

• Working directory clean (or only sprint-related changes)
• Current branch dev (or specified in sprint plan)
• All existing tests pass
• All existing linting passes
• Sprint plan approved and documented
• JSON progress file created AND POPULATED by sprint-planner (not just template!)
• JSON must pass validation: scripts/validate_sprint_json.sh <sprint-id>

Failure Recovery

If Tests Fail During Sprint

1. Show test failure output
2. Ask user: "Tests failing. Options: (a) fix now, (b) revert change, (c) pause sprint"
3. Don't proceed until tests pass

If Linting Fails During Sprint

1. Show linting output
2. Try auto-fix: make fmt
3. If still failing, ask user for guidance
4. Don't proceed until linting passes

If Implementation Blocked

1. Show what's blocking progress
2. Ask user for guidance or clarification
3. Consider simplifying the approach
4. Document the blocker in sprint plan

If Velocity Much Lower Than Expected

1. Pause and reassess after 2-3 milestones
2. Calculate actual velocity
3. Propose: (a) continue as-is, (b) reduce scope, (c) extend timeline
4. Update sprint plan with revised estimates

Coordinator Integration (v0.6.2+)

The sprint-executor skill integrates with the AILANG Coordinator for automated workflows.

Autonomous Workflow

When configured in ~/.ailang/config.yaml, the sprint-executor agent:

1. Receives handoff messages from sprint-planner
2. Executes sprint plans with TDD and continuous linting
3. Creates approval request for code review before merge

coordinator:
  agents:
    - id: sprint-executor
      inbox: sprint-executor
      workspace: /path/to/ailang
      capabilities: [code, test, docs]
      trigger_on_complete: []  # End of chain
      auto_approve_handoffs: false
      auto_merge: false
      session_continuity: true
      max_concurrent_tasks: 1

Receiving Handoffs from sprint-planner

The sprint-executor receives:

{
  "type": "plan_ready",
  "correlation_id": "sprint_M-CACHE_20251231",
  "sprint_id": "M-CACHE",
  "plan_path": "design_docs/planned/v0_6_3/m-cache-sprint-plan.md",
  "progress_path": ".ailang/state/sprints/sprint_M-CACHE.json",
  "session_id": "claude-session-xyz",
  "estimated_duration": "3 days",
  "total_loc_estimate": 650
}

Session Continuity

With session_continuity: true:

• Receives session_id from sprint-planner handoff
• Uses --resume SESSION_ID for Claude Code CLI
• Preserves full conversation context from design → planning → execution
• Maintains understanding of design decisions and rationale

Human-in-the-Loop

With auto_merge: false:

1. Sprint is executed in isolated worktree
2. All milestones completed with tests passing
3. Approval request shows:
   • Git diff of all changes
   • Test results
   • CHANGELOG updates
4. Human reviews implementation quality
5. Approve → Changes merged to main branch
6. Reject → Worktree preserved for fixes

End of Pipeline

As the last agent in the chain:

• trigger_on_complete: [] means no automatic handoff
• Final approval merges directly to main branch
• Sprint JSON updated to status: completed
• Design docs moved to implemented/ directory

Notes

• This skill is long-running - expect it to take hours or days
• Pause points are built in - you're not locked into finishing
• Sprint plan is the source of truth - but reality may require adjustments
• Git commits create a reversible audit trail
• TodoWrite provides real-time visibility into progress
• Test-driven development is non-negotiable - tests must pass
• Multi-session continuity - Sprint can span multiple Claude Code sessions (NEW)
• JSON state tracking - Structured progress in .ailang/state/sprints/sprint_<id>.json (NEW)