Automated Project Planning and Daily Code Review with Fable's /goal and /loop Commands

Workflow value: 85/100
Status: active · Freshness: 70/100 · Confidence: 0.90 · Level: advanced
Categories: Quality Control, Token Saving, Context & Memory, Debugging, Multi-Agent
Original source: r/ClaudeAI post/comment

What problem this solves

Automating comprehensive project planning, task breakdown, continuous code review, testing, and daily issue tracking for large codebases using Fable's /goal and /loop commands.

Summary

The user describes a workflow leveraging Fable's /goal command for detailed project planning, task generation, dependency analysis, and a structured task lifecycle (commit, review, test, fix). They also detail a /loop command for daily automated code review, bug identification, task creation, and work log generation, utilizing a spawned Sonnet agent.

Why it is useful

This workflow provides concrete, detailed examples of how to leverage Fable's powerful /goal and /loop slash commands for comprehensive software development tasks. It outlines a structured approach to project planning, task breakdown, continuous code review, automated testing, and daily issue tracking. The specific command parameters and sub-steps make it highly actionable and transferable for users looking to integrate AI into their development lifecycle, especially for managing large or complex repositories.

Workflow

1. Initiate a chat with Fable (suggested 'high effort' setting).
2. Provide Fable with a high-level project description and ask for epics/tasks, emphasizing deep research and enterprise product considerations.
3. Execute the /goal command with the following instructions:
   1. Read the current session and create a checklist from all important information.
   2. Start writing all tasks mentioned into a 'tasks' directory (create if it doesn't exist).
   3. Before starting, review tasks and find blind spots using a dependencies graph, issue tree, and decision table.
   4. Follow a task life cycle: after finishing each task, commit it, review it, write a test, and test it. If okay, take the next task; otherwise, run the loop again and fix the issue.
4. Set up a daily /loop command (e.g., '/loop 1d at 08:00') with the following actions:
   1. Spawn a Sonnet 4.6 agent (high effort).
   2. Load the last day's work log.
   3. Review all commits from the past 24 hours.
   4. If any issues or bugs are found, create a task in the 'tasks' directory and set related tags.
   5. Write a work log with the exact date and time (using the 'date' command).

Tools / artifacts

• Fable AI
• Sonnet 4.6 agent
• /goal command
• /loop command
• tasks directory
• work log
• dependencies graph
• issue tree
• decision table
• Git commits

Validation signals

• User states 'The result was unbelievable'
• User plans to share results on Github soon

Limitations

• The 'massive repo' context is mentioned, but details on how Fable handles context limits for such a repo are not provided.
• The actual output or results of the workflow are not yet shared, only promised.
• The 'high effort' setting for Fable is vague and noted by the author as token-intensive, which could be a cost concern.
• The full context provided to Fable during the initial chat is not detailed, only the prompt.
• The post is an initial experience report rather than a fully documented guide.

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