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openclaw-insightOpenClaw insight 搜索

Agent Skill

openclaw-insight 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

8,504

周安装

344

GitHub Stars

公开资料未说明

下载量

2,669
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:openclaw-insight(OpenClaw insight 搜索)
来源仓库:https://github.com/linsheng9731/openclaw-insight
安装命令:
openclaw skills install openclaw-insight
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install openclaw-insight

简介

OpenClaw insight 分析使用模式并生成交互式洞察报告。

  • 适用于会话统计、行为分析与效率瓶颈识别需求。
  • 通过 clawhub 安装后启动可视化服务展示图表与趋势线。
  • 需授权读取历史消息数据库,注意保护用户隐私数据。
  • 建议定期归档报告文件以防存储空间耗尽。openclaw-insight 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
openclaw-insight
description
|

OpenClaw Insight — Usage Guide

CLI tool that analyzes local OpenClaw session history and generates interactive reports with usage statistics, behavior patterns, friction analysis, and improvement suggestions. 100% local — no data leaves your machine.

Installation

One-Click Install (Recommended)

Use the official one-click installation script:

curl -fsSL https://raw.githubusercontent.com/linsheng9731/openclaw-insight/main/install.sh | bash

This script will automatically:

  1. Detect your operating system and architecture
  2. Download the appropriate binary release
  3. Verify the integrity of the downloaded file
  4. Install it in a suitable location ($HOME/.local/bin by default)
  5. Make the command available in your PATH

Install Specific Version

To install a specific version (e.g., v1.0.0):

curl -fsSL https://raw.githubusercontent.com/linsheng9731/openclaw-insight/main/install.sh | bash -s -- --version v1.0.0

From Source

For development or if you want to build from source:

git clone https://github.com/linsheng9731/openclaw-insight.git
cd openclaw-insight
npm install && npm run build

CLI Usage

# Default: analyze last 30 days, open HTML report in browser
openclaw-insight

# Analyze last 7 days
openclaw-insight --days 7

# JSON output
openclaw-insight --format json --output report.json

# Specific agent + custom output
openclaw-insight --agent my-agent --output ~/Desktop/insight.html

# Verbose, no auto-open
openclaw-insight --verbose --no-open

Options

OptionDefaultDescription
-d, --days <n>30Number of days to analyze
-m, --max-sessions <n>200Maximum sessions to process
-a, --agent <id>auto-detectAgent ID to analyze
-s, --state-dir <path>~/.openclawOpenClaw state directory
-o, --output <path>~/.openclaw/usage-data/report.htmlOutput file path
-f, --format <fmt>htmlOutput format: html or json
--no-openDon not auto-open the report in browser
-v, --verboseEnable verbose output

What the Report Includes

Usage Statistics

  • Sessions: total count, daily average, activity streaks
  • Tokens: input/output breakdown, cache hit rates, cost estimation
  • Temporal: daily activity charts, peak hours identification
  • Channels: per-channel session counts and token efficiency
  • Models: model diversity, per-model cache performance

Behavior Patterns

Automatically detects: peak hours, channel preferences, session duration profiles, cache utilization efficiency, model diversity, and tool usage preferences. Each pattern has an impact level (high / medium / low).

Friction Events

Identifies pain points in your sessions:

TypeDescription
high_token_wasteExcessive output relative to input
excessive_compactionsRepeatedly hitting context window limits
abandoned_sessionStarted but barely used sessions
underutilized_cacheLarge sessions with zero cache hits
context_overflowRepeated context window exhaustion
single_message_sessionsOne-shot interactions with high overhead

Improvement Suggestions

Prioritized recommendations across these categories:

  • Token Efficiency — cache optimization, verbosity control, batching
  • Channel Optimization — multi-channel access, per-channel efficiency
  • Model Selection — routing simple tasks to cheaper models
  • Context Management — conversation splitting, token budgets
  • Scheduling — usage pattern optimization
  • Memory Utilization — cross-session context retention
  • Feature Discovery — underused OpenClaw capabilities
  • Workflow Improvement — conversation depth, specification clarity

Each suggestion includes impact, effort, detailed explanation, and optional config snippets.

Data Sources

The tool reads from OpenClaw local state directory (read-only, never modifies data):

~/.openclaw/
  agents/{agentId}/
    sessions/
      sessions.json          # Session metadata index
      {sessionId}.jsonl      # Per-session conversation transcripts

JSON Output Structure

When using --format json, the report contains:

InsightReport {
  generatedAt, periodStart, periodEnd, daysAnalyzed,
  summary        — aggregate stats (sessions, tokens, cost, streaks, etc.)
  dailyActivity  — per-day breakdown
  hourlyDistribution — 24-hour activity heatmap
  channelStats   — per-channel metrics
  modelStats     — per-model metrics
  sessionAnalyses — detailed per-session data
  patterns       — detected behavior patterns
  frictions      — friction events
  suggestions    — improvement recommendations
}

Common Scenarios

User RequestCommand
Show my statsopenclaw-insight
How much am I spending?openclaw-insight --format json then read summary.estimatedCostUsd
Why are my sessions slow?Run analysis then focus on friction events
Compare my channelsRun analysis then present channelStats
Report for last weekopenclaw-insight --days 7
How can I use OpenClaw better?Run analysis then present top suggestions

Troubleshooting

ProblemFix
No agents foundVerify ~/.openclaw exists and contains agent data
No sessions in last N daysIncrease --days value
Empty channel/model statsOpenClaw version may be too old
Build errorsUpgrade to Node.js >= 22

Development

npm install          # Install dependencies
npm run build        # Build
npm run dev          # Development mode
npm test             # Run tests
npm run clean        # Clean build artifacts

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

83.94%
按下载量换算2,240

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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