Analyze agent-user conversation transcripts to identify skill gaps and failure patterns.
npx skills add https://github.com/strawgate/agent-skills --skill transcript-audit
Please help me install this Agent Skill. Skill: transcript-audit Source: https://github.com/strawgate/agent-skills/tree/main/transcript-audit Command: npx skills add https://github.com/strawgate/agent-skills --skill transcript-audit
This skill addresses the gap between how AI agents are currently performing and how users actually interact with them, identifying patterns of confusion, failure, and unmet needs.
Use the transcript-audit skill to find all local agent transcripts and generate a summary of the top task categories and missing capabilities.
High-intent search queries and answers about installing and using this skill.
To analyze agent transcripts, extraction scripts process JSON and JSONL conversation logs to identify recurring task categories, context gaps, and specific failure signals in agent-user interactions. This yields actionable improvement recommendations for existing skill prompts.
Yes, transcript discovery automatically locates and extracts conversation logs from various AI coding tools like OpenCode, Cline, and Claude Desktop. The extraction scripts process these local JSON and JSONL logs into evaluated interaction data.
Yes, you need Python 3 installed to run the Python-based extraction scripts. These scripts are required to process JSON and JSONL logs into actionable improvement recommendations for your AI coding agents.
The best way to optimize AI agent performance is to audit historical conversation transcripts to identify patterns of confusion and unmet needs. This provides a structured framework to propose concrete changes to existing skill prompts and logic.
Transcript analysis proposes changes to skill prompts by evaluating real-world usage data from agent-user interactions. It identifies recurring task categories and missing capabilities, providing a structured framework to update skill logic accordingly.
The extraction scripts support processing JSON and JSONL log formats. They extract and sample interaction data from these file formats to identify skill gaps and failure patterns across multiple AI coding tool environments.
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