Previously NAG_REMINDER was only checked in main() after a task completed,
meaning models never saw the reminder during long-running tasks.
Now NAG_REMINDER is injected inside agent_loop when rounds_without_todo > 10,
so models see it during task execution (matching Kode's behavior).
Fixes#14
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Tests:
- test_bash_echo: Run simple bash command
- test_file_creation: Create and verify file
- test_directory_listing: List directory contents
- test_file_search: Search with grep
- test_multi_step_task: Multi-step file manipulation
Each test runs a complete agent loop (API call -> tool execution -> continue).
Required secrets:
- TEST_API_KEY: API key for testing
- TEST_BASE_URL: API base URL
- TEST_MODEL: Model (default: claude-3-5-sonnet-20241022)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Remove provider_utils.py (241 lines of adapter code)
- Simplify all agent files to use Anthropic SDK directly
- Update model to claude-sonnet-4-5-20250929
- Add python-dotenv with override=True (.env takes priority over env vars)
- Simplify .env.example to only require ANTHROPIC_API_KEY
This keeps the codebase focused on teaching agent concepts
rather than API compatibility layers. Users who need other
providers can use tools like litellm or one-api.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Remove all reverse-engineered Claude Code source code
- Replace with 100% original educational content from mini-claude-code
- Add clear disclaimer: independent project, not affiliated with Anthropic
- 5 progressive agent implementations (v0-v4, ~1100 lines total)
- Include agent-builder skill for teaching agent construction
- Bilingual documentation (EN + ZH)
This repository now focuses purely on teaching how modern AI agents work
through original, from-scratch implementations.
Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
