How do I install the Alibabacloud Adb Openclaw Insight skill?

Run npx skillmds@latest add aliyun/alibabacloud-adb-openclaw-insight in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Alibabacloud Adb Openclaw Insight safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Alibabacloud Adb Openclaw Insight?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Alibabacloud Adb Openclaw Insight free to use?

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Who published Alibabacloud Adb Openclaw Insight?

aliyun (@aliyun) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Alibabacloud Adb Openclaw Insight by aliyun

Name: Alibabacloud Adb Openclaw Insight
Rating: 4.2 (5 reviews)
Author: aliyun

Alibabacloud Adb Openclaw Insight

OpenClaw conversation log collection and deep insight analysis Skill. Collects OpenClaw session logs (JSONL format) in real time and pushes them to Alibaba Cloud AnalyticDB MySQL (ADB) for storage. Provides a three-layer insight analysis architecture: L1 Operational Efficiency (Token efficiency, session depth, tool chain analysis, high-cost attribution, anomaly detection), L2 User Behavior (intent classification, task complexity, success rate, prompt quality, topic clustering, retry detection, thinking depth, user maturity), and L3 Organizational Cognition (tech stack heatmap, knowledge gap discovery, best practice extraction, skill candidate discovery, narrative report generation). Powered by SQL + Python + LLM. Use this Skill when you need to monitor OpenClaw usage, analyze costs, understand user behavior patterns, or generate organizational intelligence reports.

aliyun Updated Sep 10, 2026

File contents

OpenClaw Logger Insight ADB Skill

Collect OpenClaw session logs in real time and push them to AnalyticDB MySQL. Analyze usage patterns with a three-layer insight architecture powered by SQL + Python + LLM.

Prerequisites

Python >= 3.10 (use python or python3 depending on your system)
An accessible Alibaba Cloud AnalyticDB MySQL instance
OpenClaw deployed and generating session files (~/.openclaw/agents/*/sessions/*.jsonl) and logs (/tmp/openclaw/openclaw-YYYY-MM-DD.log)
(Optional) An OpenAI-compatible or Anthropic LLM API endpoint for L2/L3 analysis

Quick Start

# 1. Install uv package manager
curl -LsSf https://astral.sh/uv/install.sh | sh

# 2. Install dependencies
uv pip install -r requirements.txt

# 3. Copy the configuration template
cp config.example.json config.json
# Edit config.json: fill in ADB connection details and (optionally) LLM API config

# 4. Initialize the database tables
uv run python -m scripts.init_db

# 5. (Optional) Start the all-in-one service (collection + scheduled analysis)
uv run python -m scripts.main

CLI Commands

Collect — One-shot data collection

Scans new session JSONL files and daily log files, inserts records into ADB, saves the file-offset checkpoint, then exits. Safe to call repeatedly.

uv run python -m scripts.main collect

Analyze — Run full insight analysis

Runs the full three-layer analysis pipeline (L1 Operational → L2 Behavior → L3 Organizational → Final Report) over the configured time window.

uv run python -m scripts.main analyze

Run with a custom time range:

# Time format: YYYY-MM-DD or YYYY-MM-DD HH:MM:SS
uv run python -m scripts.analyze_usage --from "2026-03-01 00:00:00" --to "2026-03-10 23:59:59"

Final Report — Print the latest report

Fetches and prints the most recent narrative report stored in ADB.

uv run python -m scripts.main final-report

Scheduled Collection via OpenClaw Cron

python -m scripts.main collect is the recommended way to keep data flowing into ADB. It runs a single collection pass, saves the file-offset checkpoint, and exits — making it safe to call repeatedly from any scheduler.

{
  "cron": "*/30 * * * * *",
  "command": "python -m scripts.main collect",
  "cwd": "/path/to/alibabacloud-adb-mysql-mcp-server/skill/alibabacloud-adb-openclaw-insight"
}

Each invocation:

Scans new JSONL session files and daily log files since the last run
Inserts new records into ADB in batches
Saves the file-offset checkpoint (.collect_state.json) so the next run picks up exactly where this one left off
Exits cleanly — no background process to manage

Configuration

See config.example.json for all options:

adb: ADB connection (host, port, database, credentials, table name)
collection: Collection parameters (interval, batch size, retention days)
filters: Log filtering (minimum level, subsystem include/exclude)
llm: LLM API configuration (endpoint, API key, model, concurrency, temperature)
analysis: Analysis toggles (enableL1/L2/L3, analysis window days, max sessions for LLM)

Note: L1 analysis runs without LLM. L2 and L3 require a configured LLM endpoint.

---name: alibabacloud-adb-openclaw-insightdescription: OpenClaw conversation log collection and deep insight analysis Skill. Collects OpenClaw session logs (JSONL format) in real time and pushes them to Alibaba Cloud AnalyticDB MySQL (ADB) for storage. Provides a three-layer insight analysis architecture: L1 Operational Efficiency (Token efficiency, session depth, tool chain analysis, high-cost attribution, anomaly detection), L2 User Behavior (intent classification, task complexity, success rate, prompt quality, topic clustering, retry detection, thinking depth, user maturity), and L3 Organizational Cognition (tech stack heatmap, knowledge gap discovery, best practice extraction, skill candidate discovery, narrative report generation). Powered by SQL + Python + LLM. Use this Skill when you need to monitor OpenClaw usage, analyze costs, understand user behavior patterns, or generate organizational intelligence reports.---# OpenClaw Logger Insight ADB SkillCollect OpenClaw session logs in real time and push them to AnalyticDB MySQL. Analyze usage patterns with a three-layer insight architecture powered by **SQL + Python + LLM**.## Prerequisites- Python >= 3.10 (use `python` or `python3` depending on your system)- An accessible Alibaba Cloud AnalyticDB MySQL instance- OpenClaw deployed and generating session files (`~/.openclaw/agents/*/sessions/*.jsonl`) and logs (`/tmp/openclaw/openclaw-YYYY-MM-DD.log`)- (Optional) An OpenAI-compatible or Anthropic LLM API endpoint for L2/L3 analysis## Quick Start```bash# 1. Install uv package managercurl -LsSf https://astral.sh/uv/install.sh | sh# 2. Install dependenciesuv pip install -r requirements.txt# 3. Copy the configuration templatecp config.example.json config.json# Edit config.json: fill in ADB connection details and (optionally) LLM API config# 4. Initialize the database tablesuv run python -m scripts.init_db# 5. (Optional) Start the all-in-one service (collection + scheduled analysis)uv run python -m scripts.main```## CLI Commands### Collect — One-shot data collectionScans new session JSONL files and daily log files, inserts records into ADB, saves the file-offset checkpoint, then exits. Safe to call repeatedly.```bashuv run python -m scripts.main collect```### Analyze — Run full insight analysisRuns the full three-layer analysis pipeline (L1 Operational → L2 Behavior → L3 Organizational → Final Report) over the configured time window.```bashuv run python -m scripts.main analyze```Run with a custom time range:```bash# Time format: YYYY-MM-DD or YYYY-MM-DD HH:MM:SSuv run python -m scripts.analyze_usage --from "2026-03-01 00:00:00" --to "2026-03-10 23:59:59"```### Final Report — Print the latest reportFetches and prints the most recent narrative report stored in ADB.```bashuv run python -m scripts.main final-report```## Scheduled Collection via OpenClaw Cron`python -m scripts.main collect` is the recommended way to keep data flowing into ADB. It runs a single collection pass, saves the file-offset checkpoint, and exits — making it safe to call repeatedly from any scheduler.Register it as an OpenClaw cron job (example: every 30 seconds):```json{ "cron": "*/30 * * * * *", "command": "python -m scripts.main collect", "cwd": "/path/to/alibabacloud-adb-mysql-mcp-server/skill/alibabacloud-adb-openclaw-insight"}```Each invocation:1. Scans new JSONL session files and daily log files since the last run2. Inserts new records into ADB in batches3. Saves the file-offset checkpoint (`.collect_state.json`) so the next run picks up exactly where this one left off4. Exits cleanly — no background process to manage## ConfigurationSee `config.example.json` for all options:- **adb**: ADB connection (host, port, database, credentials, table name)- **collection**: Collection parameters (interval, batch size, retention days)- **filters**: Log filtering (minimum level, subsystem include/exclude)- **llm**: LLM API configuration (endpoint, API key, model, concurrency, temperature)- **analysis**: Analysis toggles (enableL1/L2/L3, analysis window days, max sessions for LLM)> **Note**: L1 analysis runs without LLM. L2 and L3 require a configured LLM endpoint.

Frequently asked questions