wjx-mcp-use

wjx-mcp-use is a skill for Claude Code, Codex from wjxcom/wjx-ai-kit. It costs 113 tokens per session (5,928 once invoked), scanned A, original, MIT.

A guide for using Wenjuanxing, a Chinese online questionnaire platform, through connected tools. It covers creating and editing surveys, reading responses, analyzing data, managing contacts, and generating sign-in links.

In plain words
What is it for?
Use it to create or update surveys, retrieve questionnaire data, manage respondents, analyze results, and generate supported login links.
Why use it?
It sets rules for building one complete survey, choosing the right format, handling unsupported question types, and checking configuration when needed.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument; mentions Codex.

Good fit Use it to create or update surveys, retrieve questionnaire data, manage respondents, analyze results, and generate supported login links.

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Install with agentmods
npx agentmods add skills/wjxcom/wjx-ai-kit/wjx-mcp-use
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 wjxcom/wjx-ai-kit --skill wjx-mcp-use
Clone the repo
git clone --depth 1 https://github.com/wjxcom/wjx-ai-kit

Made for: Claude Code, Codex.

Its marketplace also offers this one on its own, as the plugin wjx-mcp-use/plugin install wjx-mcp-use after adding the marketplace above.

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 wjx-mcp-use

README.md
[![agentmods](https://agentmods.dev/badge/skills/wjxcom/wjx-ai-kit/wjx-mcp-use/github.svg)](https://agentmods.dev/skills/wjxcom/wjx-ai-kit/wjx-mcp-use)
Your own site
<a href="https://agentmods.dev/skills/wjxcom/wjx-ai-kit/wjx-mcp-use"><img src="https://agentmods.dev/badge/skills/wjxcom/wjx-ai-kit/wjx-mcp-use/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 wjx-mcp-use

Your own site · 80×15
<a href="https://agentmods.dev/skills/wjxcom/wjx-ai-kit/wjx-mcp-use"><img src="https://agentmods.dev/badge/skills/wjxcom/wjx-ai-kit/wjx-mcp-use.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 113 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,928 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00113 $0.05928
Opus 5 $0.00056 $0.02964
Sonnet 5 $0.00023 $0.01186
Haiku 4.5 $0.00011 $0.00593

Measured today against content hash 1d8a992f33f7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

wjx-mcp-use scanned grade A with 0 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 today.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

wjx-skills/wjx-mcp-use/SKILL.md · 256 lines

How it starts

The opening of the file, as written. The whole thing — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.

wjx-mcp-server Usage Guide

wjx-mcp-server 提供 MCP 工具、参考资源和 prompt 模板,覆盖问卷星核心业务子集;CLI 是主入口,工作站能力(初始化、配置、补全、Skill 安装)保持 CLI-only。完整差异以仓库 capabilities/capability-matrix.json 为准。

HTTP 凭据边界

本地优先使用 stdio,并通过 WJX_API_KEY 提供上游凭据。HTTP 模式中,MCP_AUTH_TOKEN 只保护 /mcpAuthorization: Bearer 访问 gate;单租户上游仍使用 WJX_API_KEY。启用 MCP_TENANT_MODE=1 时,每个请求必须提供 X-WJX-API-Key,服务端按 session 隔离且不回退进程级 key。只有显式设置 MCP_LEGACY_BEARER_API_KEY=1 才允许 Bearer 兼作上游 API Key;/health 不要求 Bearer。不要在消息、日志或 URL 中输出完整凭据。

HTTP 服务配置

如果使用已部署的 MCP HTTP 服务,无需在本机安装 wjx-mcp-server 或配置本地 WJX_API_KEY。在支持 MCP HTTP 的客户端配置中添加:

{
  "mcpServers": {
    "wjx": {
      "type": "http",
      "url": "https://alifc.wjx.cn/mcp/latest",
      "headers": {
        "Authorization": "Bearer sk-wjx-xxx"
      }
    }
  }
}

sk-wjx-xxx 替换为服务端分配的 HTTP 访问令牌。保存配置后完全重启客户端;启用多租户模式时,还需按服务端要求提供 X-WJX-API-Key

Agent 前门

MCP 任务遵循“发现意图 -> 预检 -> 计划 -> 确认 -> 执行 -> 读回验证 -> 报告”。Prompt 只提供指导,不执行工具也不保证验证;Agent 必须根据工具返回的 isErrorresult 字段判断成功。WorkBuddy、Cowork、Codex Work、Qianwen Work 都先按 宿主中立握手与路由 检查真实能力,不根据宿主名称猜测配置或 API。创建、发布、提交、设置替换、清理和凭据相关操作先说明副作用,高风险和队列消费操作需要确认;网络超时后的结果按 unknown 处理并优先读回。风险、重试、验证和 JSONL 题型以生成的 agent-contract/jsonl-qtypes 资料及对应只读资源为准。 其中包括 wjx://reference/jsonl-qtypes

query_responses_realtime 会消费服务端实时答卷队列,因此 Agent contract 将它标记为高风险且不可重放;调用前先向用户说明会移除/消费队列中的记录并取得确认。该标记是 MCP/Agent 层的安全策略,不改变 CLI 的 response realtime metadata 或退出码。

外部问卷产品的常见入口可这样映射:question builder 对应 create_survey_by_json 的 JSONL;preview 对应 build_preview_url;publish 对应 update_survey_status;collect 对应 query_responses/download_responses;analyze 对应分析工具。分支、随机、配额和 piping 只有在生成 profile 明确列出并通过 SDK 校验时才可使用,否则视为未验证能力。

AI Agent 行为准则(必读)

规则 0:创建问卷只用 create_survey_by_json(强制)

当前 MCP Server 只注册 create_survey_by_json 作为问卷创建工具。create_survey_by_textcreate_survey 已移除;历史 DSL/JSON 必须在 MCP 外部转换为 JSONL。所有当前可创建题型、投票、考试、表单都走 create_survey_by_json;JSONL 不承诺覆盖读取接口的全部数字 q_type/q_subtype 编码。

Read the full file on GitHub · 256 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. today Changed · +5 lines 1d8a992f33f7
  2. 3d ago Changed · +16 lines · -5 tokens per session c16b6f7a3052
  3. 4d ago Changed · +27 lines 12545257f5b6
  4. 9d ago Changed · +1 tokens per session bf3a92178f79
  5. 12d ago First seen · 208 lines · 117 tokens per session scan A 5c41438ba53a

Subscribe to this mod's changes

wjx-mcp-use is a skill published in the GitHub repository wjxcom/wjx-ai-kit (18 stars, last pushed yesterday), licensed MIT. It adds 113 tokens to every session and 5,928 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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