magic-todo

magic-todo

Setup

• Python: /Users/alice/v/.venv-mlx-lm/bin/python
• Script: /Users/alice/v/scripts/magic_todo_mlx.py
• Default model: mlx-community/Qwen3-8B-4bit
• Elisp: /Users/alice/v/magic-todo-org/emacs/magic-todo-org.el

CLI Usage

unset PYTHONPATH

Generate JSON breakdown

echo "your task here" | /Users/alice/v/.venv-mlx-lm/bin/python
/Users/alice/v/scripts/magic_todo_mlx.py
--format json --spice 2
--model mlx-community/Qwen3-8B-4bit
--max-tokens 800

Generate org-mode checklist

echo "your task here" | /Users/alice/v/.venv-mlx-lm/bin/python
/Users/alice/v/scripts/magic_todo_mlx.py
--format md --spice 2
--model mlx-community/Qwen3-8B-4bit
--max-tokens 800

## Org File Entry Format

```org
* TODO <task description>
:PROPERTIES:
:MAGIC_TODO_TASK: <task description>
:MAGIC_TODO_SPICE: <1-5>
:MAGIC_TODO_MODEL: mlx-community/Qwen3-8B-4bit
:END:
- [ ] step one
- [ ] step two

Spice Levels

Level	Meaning	Guidance
1	Trivial	2-3 quick steps
2	Easy	4-6 clear steps
3	Medium	6-10 steps, may need substeps
4	Hard	8-15 steps with substeps
5	Overwhelming	10-20 steps, deeply broken down

Parameters

Flag	Default	Description
--format	text	Output format: text, md, json
--spice	2	Difficulty 1-5
--model	Qwen3-8B-4bit	MLX model repo id
--max-tokens	2048	Max generation tokens
--temp	0.7	Sampling temperature
--top-p	0.9	Nucleus sampling
--context	-	Existing org content for style learning
--list-models	-	List cached MLX models

Workflow

1. Run the script with --format json to get structured output
2. Parse the JSON: {"title": "...", "steps": [{"text": "...", "substeps": null}]}
3. Format as org checklist (- [ ] step text)
4. Append to the target .org file with PROPERTIES block

Output Rules

• Steps are concise (~10 words max), verb-first
• Tools are always suggested with alternatives ("using X or Y")
• No filler: no "review", "test", "document", "audit", "ensure", "plan"
• ADHD-friendly: many small steps, no walls of text

Known Org Files

• /Users/alice/vi/plurigrid.org/plurigrid-basinator.org