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Chat History Analyzer

Extracts and analyzes Cursor IDE chat history to identify key discoveries, obstacles, and solutions, saving findings to the journal.

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Extracts and analyzes Cursor IDE chat history to identify key discoveries, obstacles, and solutions, saving findings to the journal.

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Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
README.md, SKILL.md, _meta.json, scripts/analyze_logs.py, scripts/chat_history_analyzer.py, scripts/combined_analysis.py

Validation

  • Use the Yavira download entry.
  • Review SKILL.md after the package is downloaded.
  • Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. Paste one of the prompts below and point your agent at the extracted folder.
New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.5

Documentation

ClawHub primary doc Primary doc: SKILL.md 8 sections Open source page

Description

Extracts and analyzes Cursor IDE chat history to identify key discoveries, obstacles, and solutions, saving findings to the journal.

Chat History Analyzer | OpenClaw Skill

Extracts chat history from Cursor IDE's local SQLite databases, analyzes the last hour of conversations for key discoveries, obstacles, and solutions, and saves structured findings to the OpenClaw journal directory.

Usage

As a scheduled cron job to continuously track insights from chat history Manually to analyze recent chat activity To identify recurring patterns, problems, or solutions in your workflow # Combined log and chat history analysis (for cron jobs) python3 /Users/ghost/.openclaw/workspace/skills/chat-history-analyzer/scripts/analyze_logs.py # Analyze last hour of chat history only python3 /Users/ghost/.openclaw/workspace/skills/chat-history-analyzer/scripts/chat_history_analyzer.py # Analyze last 2 hours python3 /Users/ghost/.openclaw/workspace/skills/chat-history-analyzer/scripts/chat_history_analyzer.py --hours 2 # Output JSON format python3 /Users/ghost/.openclaw/workspace/skills/chat-history-analyzer/scripts/analyze_logs.py --json

What this skill does

Extracts chat history from Cursor's SQLite databases (global and workspace-specific) Analyzes the last hour of messages for patterns indicating discoveries, obstacles, and solutions Saves structured findings to /Users/ghost/.openclaw/journal/ as markdown files Runs automatically via cron job every hour

Integration as a Cron Job

This skill is designed to run hourly via OpenClaw cron. The analyze_logs.py script combines both log analysis and chat history analysis. Example Cron Job Configuration: { "payload": { "kind": "agentTurn", "message": "Run analyze_logs.py script to analyze the last hour of logs and Cursor chat history, saving findings to journal.", "model": "openrouter/google/gemini-2.5-flash", "thinking": "low", "timeoutSeconds": 180 }, "schedule": { "kind": "cron", "cron": "0 * * * *" }, "delivery": { "mode": "announce" }, "sessionTarget": "isolated", "name": "Chat History & Log Analysis" } Or run directly via shell script: # Add to crontab (crontab -e) # Run every hour at minute 0 0 * * * * /Users/ghost/.openclaw/workspace/skills/chat-history-analyzer/scripts/analyze_logs.py --json >> /Users/ghost/.openclaw/logs/analyze_logs.log 2>&1

Output Format

Findings are saved to /Users/ghost/.openclaw/journal/chat_analysis_YYYY-MM-DD_HHMMSS.md with sections for: Key Discoveries: Successful findings, realizations, and implementations Obstacles Encountered: Errors, failures, and blockers Solutions Found: Fixes, workarounds, and resolutions

Requirements

Cursor IDE installed with chat history stored locally SQLite3 available (usually pre-installed on macOS) OpenClaw journal directory writable

How it works

Connects to Cursor's SQLite databases at ~/Library/Application Support/Cursor/User/globalStorage/state.vscdb and workspace-specific databases Extracts messages from the last N hours (default: 1 hour) Analyzes message content using pattern matching for discoveries, obstacles, and solutions Saves structured markdown report to the journal directory

Category context

Messaging, meetings, inboxes, CRM, and teammate communication surfaces.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
3 Scripts2 Docs1 Config
  • SKILL.md Primary doc
  • README.md Docs
  • scripts/analyze_logs.py Scripts
  • scripts/chat_history_analyzer.py Scripts
  • scripts/combined_analysis.py Scripts
  • _meta.json Config