Log learnings, errors, and feature requests to markdown files.
npx skills add https://github.com/pengfit/cjt-skills --skill self-improvement-pengfit
Please help me install this Agent Skill. Skill: self-improvement Source: https://github.com/pengfit/cjt-skills/tree/main/self-improving-agent Command: npx skills add https://github.com/pengfit/cjt-skills --skill self-improvement-pengfit
This Skill helps in capturing learnings, errors, and feature requests to enable continuous improvement across sessions.
After encountering an issue or learning, use the skill to log it to the .learnings/ directory with appropriate categories.
High-intent search queries and answers about installing and using this skill.
To capture learnings and errors for continuous improvement, you log them from user interactions or task failures into markdown files. This supports knowledge retention by storing categorized entries in a dedicated directory.
The best way to log feature requests is to capture user requests during interactions and write them to markdown files. This enables continuous improvement by retaining knowledge of desired capabilities across sessions.
Pattern detection promotes learnings to project memory by analyzing logged entries and elevating applicable knowledge. This mechanism ensures significant errors and solutions are retained for continuous improvement.
Yes, you need user interaction to log errors and knowledge retention data. The skill requires manual input to capture learnings, errors, and feature requests from task failures into markdown storage.
You store error logging data by writing captured errors and learnings into markdown files within a designated directory. This approach enables continuous improvement and knowledge retention across development sessions.
ProyectoG007Log learnings, errors, and feature requests into markdown files.
g-lokOrganize learnings, errors, and feature requests into persistent markdown logs.
korallisImplement monitoring, logging, metrics, and tracing with Grafana and Sentry.
LGuguiGenerate feature specification documents in Markdown format.
