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review-session

Analyze opencode session transcripts for prompt effectiveness and agent performance.

8|1|Updated Feb 25, 2022
Search Tags:#session analysis#opencode#agent performance#prompt effectiveness#environmental gaps
One-click install
npx skills add https://github.com/ayubun/dotfiles --skill review-session-ayubun
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-session
Source: https://github.com/ayubun/dotfiles/tree/main/configs/opencode/skills/ed3d-session-reflection/review-session
Command: npx skills add https://github.com/ayubun/dotfiles --skill review-session-ayubun

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires opencode, ed3d-conversation-reviewer, writing-opencode-directives, python, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps analyze opencode sessions for quality, effectiveness of prompting, agent performance, and environmental gaps, providing actionable recommendations.

Core Features & Use Cases

  • Session Analysis: Analyze specified or most recent non-active opencode sessions.
  • Prompt Effectiveness: Evaluate the effectiveness of prompts used in the session.
  • Agent Performance: Assess the performance of the AI agent involved in the session.
  • Environmental Gaps: Identify gaps in the session's environment that could affect performance.
  • Use Case: For a developer looking to improve the quality of their opencode sessions, this Skill can provide insights into how to enhance future sessions.

Quick Start

To review the most recent non-active opencode session, use the 'review-session' skill.

Frequently Asked Questions about review-session

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

FAQPage Schema
How do I analyze an opencode session transcript for prompting effectiveness?▼

You can analyze opencode session transcripts for prompting effectiveness by running the review-session skill, which uses the ed3d-conversation-reviewer agent to evaluate prompt quality and agent performance. It processes JSON exports and outputs Markdown analysis.

What is opencode session analysis and when do I need it?▼

Opencode session analysis evaluates AI agent performance, prompt effectiveness, and environmental gaps in your session transcripts. You need it when debugging poor agent responses or optimizing future session configurations.

How do I review the most recent non-active opencode session?▼

To review the most recent non-active opencode session, invoke the review-session skill directly. It automatically targets the latest inactive session, processes the transcript, and generates an actionable Markdown report.

Do I need Python and the opencode CLI to review agent performance?▼

Yes, reviewing agent performance requires the opencode CLI and Python scripts to handle JSON export processing. The skill also depends on the ed3d-conversation-reviewer agent and writing-opencode-directives skill.

Can I identify environmental gaps in my AI agent's opencode session?▼

Yes, you can identify environmental gaps by analyzing session transcripts with the review-session skill. It detects missing configurations or setup issues that negatively affect agent performance and provides actionable recommendations.

What's the best way to evaluate AI agent performance in opencode?▼

The best way to evaluate AI agent performance in opencode is using session analysis tools that assess prompt effectiveness and environmental factors. The review-session skill automatically processes transcripts to generate actionable Markdown insights.

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