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lesson-capture

Extract and record validated lessons from completed tasks to AGENTS.md.

Updated Apr 14, 2026

Search Tags:#documentation #agents.md #knowledge-management #quality-gates #project-management #lessons-learned #lesson-capture

Ready to run

npx skills add https://github.com/daudaudinang/vibecode --skill lesson-capture-daudaudinang

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: lesson-capture
Source: https://github.com/daudaudinang/vibecode/tree/main/.agents/skills/lesson-capture
Command: npx skills add https://github.com/daudaudinang/vibecode --skill lesson-capture-daudaudinang

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Captures and stores validated lessons from completed tasks, ensuring only quality insights are saved to AGENTS.md.

Core Features & Use Cases

Gate-based eligibility: evaluate candidates for logging as lessons.
Classification and scope: tag lessons as PATTERN, DECISION, GOTCHA, or FAILURE with a suitable scope.
Batch approval + append: prepare a batch of validated lessons for updating AGENTS.md.

Quick Start

After finishing a task, run the capture flow to validate evidence and obtain user approval, then append the lesson to AGENTS.md.

Frequently Asked Questions about lesson-capture

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

FAQPage Schema

How do I capture lessons learned from completed tasks into a knowledge base?▼

To capture lessons learned, this Skill extracts actionable insights from completed tasks and appends them to AGENTS.md. It acts as a centralized knowledge base by validating evidence and requiring user approval before publishing to the lessons section.

What is the best way to document project decisions and failures automatically?▼

Documenting project decisions and failures is handled by classifying validated lessons as PATTERN, DECISION, GOTCHA, or FAILURE. The Skill tags these insights with a suitable scope and appends them to AGENTS.md after batch approval.

How does the gate-based eligibility process work for logging lessons to AGENTS.md?▼

Gate-based eligibility for logging lessons works by enforcing evidence, user approval, and scope validation before appending. It evaluates task candidates to ensure only quality, actionable insights are saved to AGENTS.md.

Can I use this to extract knowledge from previous conversations and sessions?▼

Yes, you can use this to extract knowledge from conversations and sessions. The Skill applies its capture flow to tasks, conversations, and sessions within a repository to validate evidence and append approved lessons to AGENTS.md.

Do I need to manually approve every lesson before it updates AGENTS.md?▼

Yes, user approval is required before lessons update AGENTS.md. The Skill prepares a batch of validated lessons and enforces evidence and scope validation, but you must approve them before they are appended to the knowledge base.

Why should I use AGENTS.md for project knowledge management instead of generic notes?▼

Using AGENTS.md for project knowledge management maintains a centralized, validated repository within your codebase. Unlike generic notes, it enforces evidence and scope validation through quality gates to ensure only actionable lessons are stored.