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code-documenter

Generate structured markdown documentation and task-specific logs for code features.

Updated Jun 22, 2026
Search Tags:#code review#AI agent#code documentation#automated documentation#task logging
One-click install
npx skills add https://github.com/matchacone/pickle-LARP --skill code-documenter-matchacone
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: code-documenter
Source: https://github.com/matchacone/pickle-LARP/tree/main/.agent/skills/code-documenter
Command: npx skills add https://github.com/matchacone/pickle-LARP --skill code-documenter-matchacone

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the documentation of code for AI agents, ensuring future work can continue seamlessly with minimal need for human intervention.

Core Features & Use Cases

  • Automated Documentation: Generates structured markdown files for each feature or task.
  • Task-Specific Logs: Creates detailed logs with key decisions, gotchas, and extension instructions.
  • Use Case: When an AI agent completes a task, use this Skill to automatically document the process, making it easier for other agents to pick up where the work left off.

Quick Start

Use the code-documenter skill to document the 'court-booking-invoice' feature after completion.

Frequently Asked Questions about code-documenter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate code documentation for AI agents?▼

Automate code documentation for AI agents by generating structured markdown files that detail features, tasks, and key decisions. This ensures future AI work can continue seamlessly without human intervention.

How do I generate task logs for completed code features?▼

Generate task logs for code features by creating detailed markdown files that capture key decisions, gotchas, and extension instructions. This provides comprehensive documentation for future reference when tasks are completed.

What is the best way to document code implementations for future AI tasks?▼

The best way to document code for future AI tasks is generating structured markdown files tailored for AI agents. This approach captures key decisions and gotchas, making it easier for other agents to resume work.

Can I use automated documentation to log key decisions and gotchas for code reviews?▼

Yes, automated documentation creates detailed logs that capture key decisions and gotchas during code implementations. These task-specific logs provide essential context for future code reviews and AI-driven development.

When do I need automated code documentation for my workflow?▼

You need automated code documentation when an AI agent completes a task and you want to automatically document the process. This makes it easier for other agents to pick up where the previous work left off.

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