alibabacloud-adb-openclaw-insight

alibabacloud-adb-openclaw-insight is a skill for Claude Code, Codex from aliyun/alibabacloud-adb-mysql-mcp-server. It costs 180 tokens per session (1,050 once invoked), scanned C, original, Apache-2.0.

A tool for collecting OpenClaw conversation logs and storing them in Alibaba Cloud AnalyticDB MySQL, a managed database service. It also analyzes those logs in layers using SQL, Python, and optionally a language model.

In plain words
What is it for?
Use it to collect OpenClaw session and daily log files, track token and session usage, and run operational or deeper usage analysis.
Why use it?
It keeps session data in one database and turns raw log files into information about how agents are being used. This removes the need to inspect many JSONL log files by hand.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to collect OpenClaw session and daily log files, track token and session usage, and run operational or deeper usage analysis.

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Install with agentmods
npx agentmods add skills/aliyun/alibabacloud-adb-mysql-mcp-server/alibabacloud-adb-openclaw-insight
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add aliyun/alibabacloud-adb-mysql-mcp-server --skill alibabacloud-adb-openclaw-insight
Clone the repo
git clone --depth 1 https://github.com/aliyun/alibabacloud-adb-mysql-mcp-server

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for alibabacloud-adb-openclaw-insight

README.md
[![agentmods](https://agentmods.dev/badge/skills/aliyun/alibabacloud-adb-mysql-mcp-server/alibabacloud-adb-openclaw-insight/github.svg)](https://agentmods.dev/skills/aliyun/alibabacloud-adb-mysql-mcp-server/alibabacloud-adb-openclaw-insight)
Your own site
<a href="https://agentmods.dev/skills/aliyun/alibabacloud-adb-mysql-mcp-server/alibabacloud-adb-openclaw-insight"><img src="https://agentmods.dev/badge/skills/aliyun/alibabacloud-adb-mysql-mcp-server/alibabacloud-adb-openclaw-insight/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for alibabacloud-adb-openclaw-insight

Your own site · 80×15
<a href="https://agentmods.dev/skills/aliyun/alibabacloud-adb-mysql-mcp-server/alibabacloud-adb-openclaw-insight"><img src="https://agentmods.dev/badge/skills/aliyun/alibabacloud-adb-mysql-mcp-server/alibabacloud-adb-openclaw-insight.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 180 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,050 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00180 $0.01050
Opus 5 $0.00090 $0.00525
Sonnet 5 $0.00036 $0.00210
Haiku 4.5 $0.00018 $0.00105

Measured 12d ago against content hash e8b76155c3e1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade C, and why

alibabacloud-adb-openclaw-insight scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

The scan reads SKILL.md. This mod also ships 15 executable files (scripts/__init__.py, scripts/analysis/__init__.py, scripts/analysis/behavior_insight.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

curl -LsSf https://astral.sh/uv/install.sh | sh

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -LsSf https://astral.sh/uv/install.sh | sh
skill/alibabacloud-adb-openclaw-insight/SKILL.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.

Read the full file on GitHub · 113 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 113 lines · 180 tokens per session scan C e8b76155c3e1

Subscribe to this mod's changes

alibabacloud-adb-openclaw-insight is a skill published in the GitHub repository aliyun/alibabacloud-adb-mysql-mcp-server (32 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 180 tokens to every session and 1,050 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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