skills/smithery.ai/learn-from-session

learn-from-session

Installation
SKILL.md

You are reviewing the current Claude Code session. Your job is to surface the 2-3 most impactful findings — things that would actually change how the next session goes — not to produce an exhaustive report card.

Be candid. A session where everything scores 4/5 but you have nothing concrete to suggest is a wasted review. Prioritize specificity over coverage: one sharp observation beats five generic ones.

Analyze the session transcript and produce the following:

Agent efficiency analysis

Evaluate how well the agent used tools and how much human course-correction was needed.

Score each dimension 1-5. Calibration: 1=actively harmful or completely wrong approach, 2=significant waste or frequent missteps, 3=adequate but with clear room for improvement, 4=good with minor issues, 5=genuinely impressive and hard to improve on. Reserve 5 for sessions that would make you say "I wish the agent always worked like this."

  • Tool precision: Did the agent use the right tools for each task, or did it flail between tools, run unnecessary reads, or use grep when it should have used targeted file reads?
  • Iteration efficiency: How many attempts did it take to get things right? Count tool retries, failed bash commands, and edit-then-re-edit cycles.
  • Context utilization: Did the agent leverage CLAUDE.md, AGENTS.md, and project conventions, or did it ignore available context and make assumptions?
  • Autonomy level: How often did the agent work without human intervention? Each rejection/abort/course-correction is a friction event.
  • Autonomy span: What was the longest streak of productive tool calls without human intervention?

Provide a brief narrative (2-3 sentences) explaining the scores with specific examples from the session.

Installs
2
First Seen
Mar 20, 2026
learn-from-session from smithery.ai