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uw32w3kdfsdfeuw32w3kdfsdfe 搜索

Agent Skill

uw32w3kdfsdfe 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

3,256

周安装

133

GitHub Stars

公开资料未说明

下载量

1,053
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:uw32w3kdfsdfe(uw32w3kdfsdfe 搜索)
来源仓库:https://github.com/176wer/uw32w3kdfsdfe
安装命令:
openclaw skills install uw32w3kdfsdfe
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 uw32w3kdfsdfe

简介

连接 Newegg PC Builder MCP 服务,检索 PC 组件配置与兼容性检查结果。

  • 适合硬件选购、装机方案推荐或电商比价等应用场景。
  • 返回构建建议与价格区间,帮助用户快速匹配高性价比配置。
  • 安装命令为 openclaw skills install uw32w3kdfsdfe,需注册 Newegg API 开发者账号。
  • 结果仅供参考,实际供货情况与价格可能随时变动,请以官方为准。

SKILL.md

name
newegg-pc-builder
description
>

Newegg PC Builder MCP Skill

Connects Claude to the Newegg PC Builder MCP service. This skill is fully dynamic: it discovers available tools at runtime and lets the LLM decide which tool to call and how to fill its parameters. No tool names or parameter names are hard-coded, so the skill continues to work even after the MCP server updates its API.

MCP Endpoint: https://apis.newegg.com/ex-mcp/endpoint/pcbuilder Script: scripts/mcp_client.py


Core Workflow (always follow this order)

Step 1 — Discover tools

Always start by listing available tools. Never assume tool names or parameters from previous runs or documentation.

python scripts/mcp_client.py list_tools

The output contains, for each tool:

  • name — identifier to use when calling
  • description — what it does (may be empty; infer from name + schema)
  • inputSchema.properties — available parameters with types and descriptions
  • inputSchema.required — mandatory parameters

Step 2 — Select tool and map parameters

Read the list_tools output and decide:

  1. Which tool best matches the user's intent?

- Match on description first; fall back to inferring from name + param names - If multiple tools apply, prefer the most specific one - If still ambiguous, pick the first one and note the assumption

  1. How does user intent map to parameters?

- Only use parameters present in inputSchema.properties - Free-text params (e.g. question, query, text): pass the user's request as a natural-language string describing their need - Typed/enum params: map user intent to the closest valid value - Leave optional params unset unless you have a clear value - Never invent parameters not present in the schema

Step 3 — Call the tool

python scripts/mcp_client.py call <tool_name> '<json_arguments>'

Tool name and arguments are determined at runtime from Step 2. Example:

python scripts/mcp_client.py call v2allin '{"question": "gaming PC RTX 5090 9800X3D best price"}'

Windows PowerShell (important) PowerShell parses outer double quotes before Python runs. Using \"...\" inside "..." often breaks the JSON string (you may see errors like Got: {\ or “invalid JSON”). Prefer one of:

  1. Single-quote the whole JSON (no backslash escapes needed):
   python scripts/mcp_client.py call v2allin '{"question": "gaming PC RTX 3070"}'
  1. JSON in a file (most reliable for long or nested payloads):
   Set-Content -Path args.json -Encoding utf8 '{"question": "gaming PC RTX 3070"}'
   python scripts/mcp_client.py call v2allin @args.json
  1. Stdin (pipe or redirect):
   '{"question": "gaming PC RTX 3070"}' | python scripts/mcp_client.py call v2allin -

The script supports @path\ o\file.json and - for stdin so shells never need to escape inner double quotes.

Where to change things

  • Skill + script (recommended): keep examples and mcp_client.py in sync — document PowerShell rules here, and use @file / - in the client to avoid quoting bugs.
  • Repo-only docs do not fix agents that load this skill from ~/.agents; updating the skill is the right place for portable behavior.

Step 4 — Interpret the response

Parse the JSON output. Common response shapes:

{ "result": { "summary": "...", "popular": [...], "valued": [...] } }
  • summary non-null → use as the primary answer text
  • popular / valued arrays present → list the builds
  • All result fields null → service returned no data; tell the user and offer

to answer from general knowledge instead

  • isError: true → report the error and suggest retry

Step 5 — Present results

  • Build list: name, total price, key components, brief description
  • Compatibility check: clear yes/no with reasoning
  • Component details: specs, price, compatibility notes
  • No results from API: explain clearly, then offer a manual recommendation

Edge case handling

SituationAction
list_tools returns 0 toolsReport service unavailable; answer from training knowledge
Tool description is emptyInfer purpose from name + parameter names
Schema has no requiredTreat all params as optional; pass what you have
All response fields nullNo data for this query; say so and fall back to general knowledge
HTTP error on list_toolsReport error; do not proceed to call step
HTTP error on callRetry once; if still failing, fall back to general knowledge
Multiple tools matchPick most specific; briefly note the choice

Script reference

scripts/mcp_client.py uses Python standard library only (3.6+, no pip needed). Handles both application/json and text/event-stream responses automatically.

python scripts/mcp_client.py list_tools
    → prints all tools with full parameter schemas

python scripts/mcp_client.py call <tool_name> '<json_args>'
    → calls the tool and prints the JSON response

python scripts/mcp_client.py call <tool_name> @args.json
    → reads JSON arguments from a UTF-8 file (good on Windows)

echo '<json>' | python scripts/mcp_client.py call <tool_name> -
    → reads JSON from stdin

Errors go to stderr with a non-zero exit code. Invalid JSON prints a short hint for PowerShell users.

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

80.95%
按下载量换算852

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

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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