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Releases: ThomasRohde/klondike-spec-cli

v0.2.11 - Feature Prompt Command

08 Dec 06:13

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✨ Added

  • \klondike feature prompt \ - Generate copilot-ready prompts for implementing features
    • Includes feature description, acceptance criteria, and project context
    • Pre-commit verification instructions (lint, format, test)
    • Klondike workflow steps for feature completion
    • --output \ option to write prompt to a file
    • --interactive\ flag to launch GitHub Copilot CLI with the prompt

0.3.0: docs: improve copilot instructions based on session learnings

07 Dec 14:35

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v0.2.0

07 Dec 14:28

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v0.2.0 - MCP Server Support"

v0.1.0 - Initial Release

07 Dec 13:28

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Changelog

All notable changes to Klondike Spec CLI will be documented in this file.

The format is based on Keep a Changelog,
and this project adheres to Semantic Versioning.


0.1.0 - 2025-12-07

🎉 Initial Release

The CLI that built itself — This release represents the complete implementation of Klondike Spec CLI, developed across 4 AI coding sessions using the very methodology the tool implements.

✨ Added

Core Commands

  • klondike init [name] - Initialize .klondike directory with project artifacts
  • klondike status - Display project status with progress bar, git info, and next priorities
  • klondike validate - Check artifact integrity and consistency
  • klondike progress - Regenerate agent-progress.md from JSON data

Feature Management

  • klondike feature add - Add features with description, category, priority, and acceptance criteria
  • klondike feature list - List features with optional status filtering and JSON output
  • klondike feature show <id> - Display full feature details including verification evidence
  • klondike feature start <id> - Mark a feature as in-progress
  • klondike feature verify <id> - Mark a feature as verified with evidence
  • klondike feature block <id> - Mark a feature as blocked with reason
  • klondike feature edit <id> - Edit feature notes, priority, and criteria (description immutable)

Session Management

  • klondike session start - Begin a coding session with focus tracking
  • klondike session end - End session with summary, completed items, and handoff notes
  • Automatic git status integration shows uncommitted changes and recent commits

Reporting & Export

  • klondike report - Generate status reports in markdown, plain text, or JSON
  • klondike export-features <file> - Export features to YAML or JSON with status filtering
  • klondike import-features <file> - Import features from YAML or JSON with duplicate detection

Developer Experience

  • klondike completion <shell> - Generate shell completion scripts for bash, zsh, and PowerShell
  • Rich terminal output with colors, progress bars, and emoji icons
  • JSON output mode for programmatic integration

Quality & Reliability

  • Comprehensive input validation and sanitization
  • Git integration for status tracking and commit logging
  • Performance-optimized O(1) feature lookups via indexed data structures
  • 98 tests with 74% code coverage

🔧 Technical Stack

  • Python 3.10+ with full type annotations
  • Pith (pypith) - Agent-native CLI framework with progressive discovery
  • Rich - Beautiful terminal formatting
  • PyYAML - Configuration and import/export support
  • Hatchling - Modern Python build backend

📖 Documentation

  • Comprehensive README with story-driven narrative
  • Complete command reference with examples
  • GitHub Actions CI/CD for testing and PyPI publishing
  • MIT License

Development Journey

This project was developed in 4 AI coding sessions:

Session Focus Features Added
1 Project foundation Core models, init, status, feature CRUD
2 Session management Session start/end, progress regeneration
3 Validation & reporting Validate command, report generation
4 Polish & complete Git integration, completion, import/export, performance

Final stats:

  • 30 features specified and verified
  • 98 tests passing
  • 74% code coverage
  • 1600+ lines of Python

The Meta-Achievement

This CLI was built by an AI agent following the Klondike Spec methodology — tracking its own features, managing its own sessions, and providing verification evidence for each completed feature.

Built with 🤖 by AI, for AI, verified by humans