skills.rest
ramakay
ramakayCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

conversation-analyzer

Analyze Claude Code conversation JSONL files to extract structured data and generate problem-solution narratives.

220|27|Updated Jul 25, 2025
Search Tags:#developer tools#knowledge management#Claude AI#semantic search#conversation analysis#context retention#problem-solution
One-click install
npx skills add https://github.com/ramakay/claude-self-reflect --skill conversation-analyzer-ramakay
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: conversation-analyzer
Source: https://github.com/ramakay/claude-self-reflect/tree/main/docs/design/conversation-analyzer
Command: npx skills add https://github.com/ramakay/claude-self-reflect --skill conversation-analyzer-ramakay

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Claude often "forgets" past conversations, leading to repetitive explanations and lost context. This Skill solves that by automatically analyzing your Claude Code conversations, extracting key insights, and generating structured narratives. This ensures Claude has a perfect, searchable memory of all your past interactions, saving you time and reducing the frustration of re-explaining context.

Core Features & Use Cases

  • Automated Context Retention: Transforms raw conversation logs into rich, problem-solution narratives, making every past discussion instantly searchable and accessible to Claude.
  • Structured Data Extraction: Automatically identifies files touched, tools used, and errors encountered during a conversation, providing a comprehensive overview of past work.
  • Use Case: After a complex debugging session, use this Skill to automatically summarize the problem, attempted solutions, and the final fix. When a similar issue arises months later, Claude can instantly recall the exact steps and solutions from your past, allowing you to focus on new challenges.

Quick Start

Analyze the attached conversation project_refactor_log.jsonl to create a detailed, searchable narrative of the refactoring process.

Frequently Asked Questions about conversation-analyzer

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

FAQPage Schema
How do I extract structured data from Claude conversation logs for searchability?▼

Conversation analyzer processes Claude Code JSONL files to extract problem-solution narratives, touched files, tool usage counts, and error snapshots. The output generates structured data ready for semantic search indexing, making past interactions instantly searchable and accessible.

Can I automatically summarize debugging sessions and past solutions from conversation files?▼

Yes. The analyzer transforms raw multi-turn conversations—including user messages, assistant responses, tool traces, and code blocks—into rich narratives that capture the problem, attempted solutions, and final resolution, enabling instant recall of past fixes.

What data does the analyzer extract from Claude Code conversations?▼

The analyzer extracts timelines, files read/edited/created, tool usage counts, error detection with resolution signals, code-block presence, and token-budget-aware trimming metadata. All output is structured for downstream ingestion and semantic indexing.

How does conversation analysis help reduce repetitive explanations in ongoing projects?▼

By indexing past conversation narratives, Claude can retrieve relevant context from previous sessions automatically. This eliminates re-explaining problems and solutions, keeping focus on new challenges while maintaining perfect continuity across multiple conversations.

Can the analyzer handle multi-turn developer conversations with tool usage and code changes?▼

Yes. It processes complete developer workflows including user and assistant exchanges, tool invocations, file operations, and embedded code blocks, producing comprehensive timelines and narratives that capture the full context of complex sessions.

What format do I need for input conversation files?▼

Input conversations must be in JSONL format—Claude Code's native conversation export format. The analyzer reads each line as a complete JSON object representing a message or tool interaction in the conversation.

Related Skills

Explore More Software Engineering Skills→
oborchersoborchers
28

conversation-format

Parse Claude Code JSONL conversation files to extract text, thinking, and tool_use blocks.

Community
Advanced
KrishpotanwarKrishpotanwar

AgentDB Vector Search

Implement semantic vector search with AgentDB for document retrieval.

Community
Intermediate
pv-udpvpv-udpv
4

Remembering Conversations

Search archived Claude Code conversations with semantic vector and exact text matching.

Community
Advanced
okbest2024okbest2024

session-logs

Search and extract messages from archived JSONL session logs using jq.

Community
Intermediate