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response-analyzerReact 分析仪

Agent Skill

response-analyzer 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。

总安装

240

周安装

10

GitHub Stars

公开资料未说明

下载量

80
CodexClaudeCursorGemini CLI

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

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:response-analyzer(React 分析仪)
来源仓库:https://github.com/nguyenthienthanh/aura-frog
仓库路径:skills/response-analyzer
安装命令:
npx skills add nguyenthienthanh/aura-frog --skill "response-analyzer"
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。

AgentSkills.tonpx skills
npx skills add nguyenthienthanh/aura-frog --skill "response-analyzer"

简介

response-analyzer 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。

  • 适用于 React 项目开发、组件调试或性能分析等需要技术参考的场景。
  • 通过 npx skills add nguyenthienthanh/aura-frog --skill "response-analyzer" 安装,需确认权限范围和维护状态。
  • 使用前建议核验原始 README 和仓库内容,避免误判联网或文件读写行为。
  • 注意区分只读分析与写入变更,涉及生产环境时优先备份或事务保护。

SKILL.md

name
response-analyzer
description
MCP Response Analyzer pattern - Write large responses to temp files, load summaries into context
autoInvoke
false
priority
medium
triggers
allowed-tools
Read, Write, Bash

MCP Response Analyzer

Priority: MEDIUM - Use for large outputs Version: 1.0.0


Purpose

Reduce context bloat by:

  1. Writing large responses to /tmp/aura-frog/
  2. Loading only summaries into conversation context
  3. Referencing full data only when needed

When to Use

triggers[5]{scenario,threshold,action}:
  Command output,>100 lines,Save to temp + summarize
  API response,>5KB,Save JSON + extract key fields
  File search results,>50 files,Save list + show top 10
  Test output,>50 lines,Save full + summarize pass/fail
  Build output,>100 lines,Save full + show errors only

Temp Directory Structure

/tmp/aura-frog/
├── responses/
│   ├── cmd-{timestamp}.txt      # Command outputs
│   ├── api-{timestamp}.json     # API responses
│   └── search-{timestamp}.txt   # Search results
├── summaries/
│   └── summary-{timestamp}.md   # Generated summaries
└── session/
    └── {session-id}/            # Session-specific data

Usage Patterns

Pattern 1: Large Command Output

Before (bloats context):

npm test
# 500 lines of output loaded into context

After (optimized):

# Run and save
npm test > /tmp/aura-frog/responses/test-$(date +%s).txt 2>&1

# Load summary only
echo "Test Results Summary:"
grep -E "(PASS|FAIL|Tests:|Suites:)" /tmp/aura-frog/responses/test-*.txt | tail -10

Pattern 2: API Response Analysis

Before:

curl https://api.example.com/users
# Large JSON response in context

After:

# Save full response
curl https://api.example.com/users > /tmp/aura-frog/responses/api-$(date +%s).json

# Extract summary
jq '{total: .data | length, first_3: .data[:3] | map(.name)}' /tmp/aura-frog/responses/api-*.json

Pattern 3: File Search Results

Before:

find . -name "*.ts"
# 200+ files listed in context

After:

# Save full list
find . -name "*.ts" > /tmp/aura-frog/responses/search-$(date +%s).txt

# Show summary
echo "Found $(wc -l < /tmp/aura-frog/responses/search-*.txt) TypeScript files"
echo "Sample:"
head -10 /tmp/aura-frog/responses/search-*.txt

Commands

Save Response

# Save command output
bash scripts/response-save.sh "npm test" "test-results"

# Output:
# Saved to: /tmp/aura-frog/responses/test-results-1234567890.txt
# Summary: 150 tests, 148 passed, 2 failed

Load Summary

# Get summary of saved response
bash scripts/response-summary.sh test-results-1234567890

# Output:
# File: test-results-1234567890.txt
# Size: 45KB
# Lines: 500
# Key findings: 2 failed tests in auth.test.ts

Reference Full Data

# When full data needed
cat /tmp/aura-frog/responses/test-results-1234567890.txt

Integration with Workflow

workflow_integration[4]{phase,use_case,pattern}:
  Phase 5a (Tests),Save test output,Pattern 1
  Phase 6 (Review),Save linter output,Pattern 1
  Phase 7 (Verify),Save coverage report,Pattern 1
  Any,Large API responses,Pattern 2

Cleanup

# Auto-cleanup old files (run daily)
find /tmp/aura-frog -mtime +1 -delete

# Manual cleanup
rm -rf /tmp/aura-frog/responses/*

Token Savings

savings[4]{scenario,without,with,saved}:
  500-line test output,~2000 tokens,~100 tokens,95%
  Large JSON response,~5000 tokens,~200 tokens,96%
  200 file search,~800 tokens,~100 tokens,87%
  Build log,~3000 tokens,~150 tokens,95%

Best Practices

  1. Always summarize first - Load full data only if needed
  2. Use timestamps - Prevent file collisions
  3. Clean up regularly - Don't let temp grow
  4. Reference by ID - "See test-results-1234567890 for full output"

Note: This pattern is especially useful during TDD phases where test output can be verbose.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

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

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

Claude Code

26.02%
按下载量换算21

OpenCode

25.49%
按下载量换算20

windsurf

16.27%
按下载量换算13

cline

14.04%
按下载量换算11

Codex

8.7%
按下载量换算7

Antigravity

3.89%
按下载量换算3

安全审计

暂无安全审计结果可展示。

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。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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