# Planning Phase Summary

**Feature**: 001-llm-commit-messages
**Branch**: `001-llm-commit-messages`
**Date**: 2025-11-28
**Status**: ✅ COMPLETE - Ready for implementation

## Overview

Successfully completed planning phase for LLM-powered commit message generator feature. All required deliverables produced and validated against constitution requirements.

## Deliverables Completed

### Phase 0: Research ✅

**File**: [research.md](research.md)

Researched and documented technical decisions for:
- ✅ LLM provider integration (LiteLLM chosen)
- ✅ Git operations (subprocess with git CLI)
- ✅ Configuration management (tomllib/tomli with TOML)
- ✅ Clipboard operations (pyperclip with graceful degradation)
- ✅ Prompt design patterns (structured system/context/task)
- ✅ Token management strategy (intelligent truncation)
- ✅ Error handling patterns (actionable messages)

**Result**: All technical unknowns resolved. No NEEDS CLARIFICATION markers remain.

### Phase 1: Design ✅

#### Data Model

**File**: [data-model.md](data-model.md)

Defined entities and relationships:
- ✅ CommitMessage (generated output)
- ✅ StagedDiff (git diff input)
- ✅ CommitHistory (style context)
- ✅ RepositoryInstructions (.gmuse file)
- ✅ UserConfig (config.toml)

Includes validation rules, state transitions, and privacy considerations.

#### API Contracts

**File**: [contracts/prompt-templates.md](contracts/prompt-templates.md)

Documented prompt structure:
- ✅ Base system prompt
- ✅ Context section template
- ✅ Format-specific task prompts (freeform, conventional, gitmoji)
- ✅ Token budget allocation
- ✅ Truncation strategy
- ✅ Error handling in prompts
- ✅ Prompt assembly algorithm
- ✅ Validation rules

#### Quickstart Guide

**File**: [quickstart.md](quickstart.md)

Created user-facing getting started guide:
- ✅ 60-second quick start
- ✅ Basic workflows (standard, with hints, clipboard, formats)
- ✅ Configuration examples
- ✅ Repository-level instructions
- ✅ Common use cases
- ✅ Troubleshooting
- ✅ Advanced tips

#### Agent Context Update

**File**: [/.github/agents/copilot-instructions.md](../../.github/agents/copilot-instructions.md)

- ✅ Updated with Python 3.10+ technology
- ✅ Linked to gmuse Constitution
- ✅ Included project structure
- ✅ Added relevant commands

### Constitution Validation ✅

**File**: [plan.md](plan.md) - Constitution Check section

All gates passed:
- ✅ **Code Quality Gate**: Type hints, docstrings, Ruff, mypy enforced
- ✅ **Testing Gate**: Unit + integration tests, 85% coverage target
- ✅ **UX Gate**: Complete help text, actionable errors, docs updates
- ✅ **Performance Gate**: Token limits, timeouts, intelligent truncation

**Result**: No violations. No complexity tracking required.

## Implementation Plan

**File**: [plan.md](plan.md)

Complete technical plan includes:
- ✅ Summary of feature and approach
- ✅ Technical context (language, dependencies, storage, testing, platform)
- ✅ Constitution check with all gates validated
- ✅ Project structure (documentation and source code)
- ✅ Complexity tracking (none required - all gates pass)

## Repository Structure

```
specs/001-llm-commit-messages/
├── plan.md                          ✅ Implementation plan
├── research.md                      ✅ Phase 0: Research
├── data-model.md                    ✅ Phase 1: Data model
├── quickstart.md                    ✅ Phase 1: User guide
├── contracts/
│   └── prompt-templates.md          ✅ Phase 1: API contracts
├── checklists/
│   └── requirements.md              ✅ Spec validation
└── spec.md                          ✅ Feature specification
```

## Key Decisions Summary

| Area | Decision | Rationale |
|------|----------|----------|
| LLM Provider | LiteLLM | Unified interface, 100+ providers, auto-detection |
| Git Operations | subprocess + CLI | Universal availability, no dependencies |
| Config Format | TOML | Stdlib support, human-friendly, XDG compliant |
| Clipboard | pyperclip (optional) | Cross-platform, graceful degradation |
| Prompt Design | Structured sections | Clear system/context/task separation |
| Token Management | Intelligent truncation | Preserve structure, warn users |
| Error Messages | Actionable guidance | 95% self-service resolution target |

## Next Steps

### Phase 2: Tasks (NOT done by /speckit.plan)

Run `/speckit.tasks` command to generate:
- Detailed implementation tasks
- Task dependencies
- Acceptance criteria per task
- Estimated effort

### Implementation

After tasks are generated:
1. Review and prioritize tasks
2. Assign tasks to developers
3. Implement following TDD approach (tests first)
4. Ensure 85% coverage for all new modules
5. Update documentation as implementation progresses
6. Run constitution checks before PR merge

## Validation Checklist

- [x] All Phase 0 research complete (no NEEDS CLARIFICATION)
- [x] All Phase 1 design artifacts created
- [x] Constitution gates validated (all pass)
- [x] Agent context updated
- [x] Project structure documented
- [x] Technical decisions documented with rationale
- [x] User documentation created
- [x] API contracts defined
- [x] Data model complete with validation rules

## Metrics

- **Planning Duration**: Single session (2025-11-28)
- **Documents Created**: 7 files (plan, research, data-model, quickstart, contracts, checklist, summary)
- **Constitution Gates**: 4/4 passed
- **User Stories**: 8 prioritized (P1-P3)
- **Functional Requirements**: 20 documented
- **Success Criteria**: 9 measurable outcomes
- **Test Files Planned**: 5 unit + 1 integration
- **New Source Modules**: 4 (config, git_utils, prompt_builder, llm_client)

## Risk Assessment

### Low Risk ✅
- All dependencies have Python package availability
- No breaking changes to existing code
- XDG compliance standard across platforms
- Constitution fully satisfied

### Mitigations in Place ✅
- Optional dependencies for LLM/clipboard (graceful degradation)
- Intelligent diff truncation (token limits)
- Clear error messages (95% self-service)
- Comprehensive test strategy (85% coverage)

## Conclusion

Planning phase complete and validated. Implementation ready to proceed.

**Recommendation**: Run `/speckit.tasks` to generate detailed implementation tasks, then begin development starting with P1 user story (basic message generation).
