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Agent Skill · 研究检索

har-replay(哈尔重播)

har-replay 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

har-replay 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 52,216。

总安装 563周安装 23GitHub Stars 5,832下载 182核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:har-replay(哈尔重播)
来源仓库:https://github.com/lightdash/lightdash
仓库路径:skills/har-replay
安装命令:
npx skills add https://github.com/lightdash/lightdash --skill har-replay
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/lightdash/lightdash --skill har-replay

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

har-replay 用于查找、检索和筛选相关信息,适合根据关键词快速定位候选结果。适用于 Codex、Claude、Cursor 和 Gemini CLI 中需要线索驱动搜索的任务场景。通过 GitHub 安装,使用 npx skills add 命令添加技能。

使用前需确认权限范围、维护状态,以及是否触发联网、命令执行或文件读写。建议结合来源仓库和原始 README 进一步核验具体功能和限制。

来源仓库内路径:skills/har-replay

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/lightdash/lightdash --skill har-replay;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

har-replay 怎么安装?

在终端执行 npx skills add https://github.com/lightdash/lightdash --skill har-replay。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

har-replay 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

har-replay 需要什么权限?

权限级别是操作浏览器。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。

har-replay 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

har-replay 用的人多吗?

公开数据是累计安装 563 次,近一周安装 23 次,下载 182 次,GitHub 5,832 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

har-replay 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 5,832 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
har-replay

哈尔重播 · 本页

5635,832操作浏览器未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

HAR Replay

Replay a HAR file as a mock Lightdash backend so the frontend renders with exact production data. No database, warehouse, or authentication needed.

The user must provide a path to a .har file. If not provided as $ARGUMENTS, ask for it.

Step 1: Analyze the HAR file

Run a Python script to extract key information from the HAR:

import json, sys, re
from collections import Counter
from urllib.parse import urlparse

har_path = "$HAR_FILE_PATH"
with open(har_path) as f:
    har = json.load(f)

entries = har['log']['entries']

# Extract the page URL from the HAR pages section
page_path = None
pages = har['log'].get('pages', [])
for p in pages:
    title = p.get('title', '')
    parsed = urlparse(title)
    if parsed.path and parsed.path != '/':
        page_path = parsed.path
        break

# Fallback: extract from referer headers
if not page_path:
    for e in entries:
        for h in e['request']['headers']:
            if h['name'].lower() == 'referer':
                parsed = urlparse(h['value'])
                if parsed.path and parsed.path != '/':
                    page_path = parsed.path
                    break
        if page_path:
            break

# Find the origin (first API call)
origin = None
for e in entries:
    url = urlparse(e['request']['url'])
    if url.path.startswith('/api/'):
        origin = f"{url.scheme}://{url.netloc}"
        break

# Filter to origin entries only
api_entries = [e for e in entries if origin and origin in e['request']['url']]

# Find dashboard URL if present
dashboard_uuid = None
for e in api_entries:
    path = urlparse(e['request']['url']).path
    m = re.search(r'/dashboards/([0-9a-f-]{36})', path)
    if m:
        dashboard_uuid = m.group(1)
        break

# Find project UUID
project_uuid = None
for e in api_entries:
    path = urlparse(e['request']['url']).path
    m = re.search(r'/projects/([0-9a-f-]{36})', path)
    if m:
        project_uuid = m.group(1)
        break

# Count request types
methods = Counter()
api_paths = Counter()
has_base64 = False
post_endpoints_needing_body_match = []

for e in api_entries:
    method = e['request']['method']
    path = urlparse(e['request']['url']).path
    methods[method] += 1
    normalized = re.sub(r'[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}', '{uuid}', path)
    api_paths[f'{method} {normalized}'] += 1
    if e['response']['content'].get('encoding') == 'base64':
        has_base64 = True

# Find POST endpoints with multiple entries (need body-based matching)
for key, count in api_paths.items():
    if key.startswith('POST') and count > 1:
        post_endpoints_needing_body_match.append((key, count))

print(f"Page path: {page_path}")
print(f"Origin: {origin}")
print(f"Total API entries: {len(api_entries)}")
print(f"Project UUID: {project_uuid}")
print(f"Dashboard UUID: {dashboard_uuid}")
print(f"Has base64 content: {has_base64}")
print(f"Methods: {dict(methods)}")
print(f"POST endpoints needing body match: {post_endpoints_needing_body_match}")
print()
print("API paths:")
for p, c in sorted(api_paths.items()):
    print(f"  {p}: {c}")

Report the findings to the user:

  • Page path extracted from the HAR (this is the URL the user was viewing when the HAR was captured)
  • Origin domain
  • Number of API entries
  • Notable POST endpoints that need body-based matching (e.g., dashboard-chart with multiple chart tiles)

Step 2: Write a tailored replay server

Based on the analysis, write a replay server to scripts/har-replay-server.ts. The server must handle these concerns:

Core structure

import http from 'node:http';
import fs from 'node:fs';
import path from 'node:path';

Use only Node.js built-in modules. Run with npx tsx scripts/har-replay-server.ts <har-path>.

HAR parsing rules

  1. Filter by origin: Only index entries matching the detected origin domain
  2. Base64 decoding: Check entry.response.content.encoding === 'base64' and decode with Buffer.from(text, 'base64').toString('utf-8')
  3. Skip pending poll responses: For GET /api/v2/projects/{uuid}/query/{uuid} endpoints, parse the response body and skip entries where results.status === 'pending' — only keep the final ready response
  4. Normalize 304s to 200: Serve 304 responses as 200 (they have full body in HAR)
  5. Strip transport headers: Remove :pseudo-headers, transfer-encoding, content-encoding, content-length from response headers

Request matching strategy

  • GET requests: Match by exact "METHOD /path?query". Fall back to path without query string.
  • POST dashboard-chart: These all hit the same URL but carry different chartUuid in the request body. Index by chartUuid from the HAR request body, and match incoming requests by parsing their body.
  • POST dashboard-sql-chart: Same pattern but with savedSqlUuid. If there's only one, exact path match works.
  • Other POST requests (e.g., availableFilters): Usually unique paths, exact match works.
  • Any POST endpoint the analysis identified as having multiple entries to the same path: Must use body-based matching on a distinguishing field.

Server behavior

  • Listen on port 3001
  • Log every request with method, path, and whether it matched
  • Return {"status":"error","error":{"message":"HAR replay: no matching entry"}} for 404s
  • On startup, print the number of indexed responses and the dashboard URL to navigate to

Step 3: Start the replay server and frontend

  1. Kill any existing processes on port 3001
  2. Start the replay server in the background: npx tsx scripts/har-replay-server.ts <har-path>
  3. Start the Vite frontend dev server pointing at the replay server: PORT=3001 pnpm -F frontend dev
  4. Wait for both to be ready, then verify with: curl -s http://localhost:3001/api/v1/health

Step 4: Provide the URL

Once both servers are confirmed running, tell the user the URL to open in their browser. Construct it from the page path extracted in Step 1:

http://localhost:<vite-port><page-path>

For example, if the HAR was captured on /projects/abc-123/dashboards/def-456/view, the URL would be http://localhost:3002/projects/abc-123/dashboards/def-456/view.

Note: Vite may pick a port other than 3000 since 3001 is in use. Check the Vite startup output for the actual port.

Step 5: Debug any rendering errors

If the user reports errors:

  1. Check the replay server logs for 404s (missing HAR entries)
  2. Check for response format issues (base64 encoding, unexpected MIME types)
  3. Fix the replay server script and restart

Notes

  • The replay server is disposable — it's tailored to the specific HAR file and can be deleted after use
  • HAR files may contain session cookies and sensitive data — do not commit them
  • The frontend will 404 on any navigation away from the captured pages
  • To re-capture: Chrome DevTools > Network tab > right-click > "Save all as HAR with content"

平台分布

Codex

39.01%
按下载量换算71

Claude

30.53%
按下载量换算56

Cursor

18.91%
按下载量换算34

Gemini CLI

8.86%
按下载量换算16

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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