project-logger

name	project-logger
description	Guidelines for maintaining a transparent development log in RESOLUTION.md for stakeholders and hiring teams.
version	1.0.0
license	MIT

Project Logger Guidelines

This skill provides instructions on how to maintain a high-quality, transparent development log in RESOLUTION.md. This is critical for demonstrating architectural thinking, process management, and effective use of AI tools.

Log Structure

The RESOLUTION.md file should be organized into:

• Timeline: A chronological list of key milestones with timestamps.
• Architectural Decisions: Deep dives into why specific libraries or patterns were chosen.
• Tools Used: Accountability for AI assistance and other specialized tooling.
• Challenges & Solutions: Documentation of blockers and how they were overcome.

Writing Principles

1. Be Precise: Use 24-hour timestamps (e.g., 2026-05-22 14:30).
2. Action-Oriented: Use verbs like Implemented, Refactored, Analyzed, Configured.
3. Transparency: Always document when an AI agent performed a complex task or when a specific "Agent Skill" was invoked.
4. Business Context: Explain how technical changes benefit the end-user or the business (e.g., "Performance optimization to reduce TTM").

Log Entry Examples

Standard Timeline Item

- **YYYY-MM-DD HH:MM** - 🚀 **Feature Title**: Brief description of what was accomplished and the tools involved.

Complex Entry with Sub-items

- **YYYY-MM-DD HH:MM** - 🏗️ **Core Logic Setup**: Abstracted the WDK service layer.
    - **Deliverables**: Created `src/services/wdk.ts`.
    - **Decision**: Used the Singleton pattern to ensure a single WDK instance across the app.
    - **Outcome**: Improved state consistency during wallet switching.

Maintenance Workflow

1. Pre-Task: Define the task in the log if it involves a major architectural decision.
2. Post-Task: Immediately update the log with the timestamp and outcome.
3. Commit Sync: Ideally, the log entry should coincide with the git commit message for that phase of work.

AI Role Documentation

When using AI agents, include:

• The specific model used (e.g., Gemini 1.5 Pro).
• The "Agent Skill" invoked (e.g., #expo-architect).
• What part of the generated code was manually reviewed or adjusted for security.