Public Agent Skills by rohitg00 on Lightlines.
Tests the user's knowledge of a completed phase from the AI Engineering from Scratch course.
Guides learners through choosing and preparing for one of four Claude certification tracks with interactive lessons, labs, artifacts, and assessments.
Routes learners to exact curriculum lessons and the next host-appropriate command.
Maps a learner's AI and machine-learning knowledge to a suitable curriculum starting point.
Deletes specific observations from agentmemory after showing them and receiving explicit confirmation.
Teaches one interactive AI Engineering from Scratch lesson, quizzes the learner, and records their progress.
Guides a learner through one Agent Skills Engineering lesson and records evidence of completion.
Records corrections and hard-won behavioral rules as confidence-weighted lessons for similar future work.
Applies a recall-first, decision-point memory loop to nontrivial project work.
Searches agentmemory for past observations, sessions, and learnings about a topic.
Summarizes recent agent sessions for the current project by date and highlights important observations.
Save an insight, decision, or learning to agentmemory's long-term storage with searchable concept tags.
Shows recent sessions on the project as a clean timeline.
Creates a persistent AI engineering study plan that records the learner's goals, placement, and curriculum path.