# Test Ask Experts

> Validates that the project-level ask-experts MCP server is correctly registered and that each enabled expert produces a coherent answer to a canonical domain question. Use this whenever the user wants to verify the MCP wiring after a config change, env-var update, or rebuild.

- Skill: `lcpmarvel/test-ask-experts` (Agent Skill)
- Install (CLI): `npx skillmds@latest add lcpmarvel/test-ask-experts`
- Raw SKILL.md: https://api.skillmd.com/api/skills/lcpmarvel/test-ask-experts/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: lcpmarvel (https://skillmd.com/u/lcpmarvel)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/lcpmarvel/test-ask-experts

---


# Validate ask-experts-mcp end-to-end

This skill exercises the project's own `ask-experts` MCP server to confirm:

1. The MCP is registered and tools are visible in this Claude Code session
2. Each enabled expert returns a sensible, on-topic answer to a canonical question
3. No expert is silently broken (auth, network, model name typo, etc.)

## Execute the following steps

### Step 1 — Discover registered ask-experts tools

Look at your currently available tool list and identify any tool whose name starts with `ask_`. These come from this project's `.mcp.json` registration of `ask-experts-mcp`.

- **If you see zero `ask_*` tools**: the MCP isn't loaded. Tell the user:
  > No `ask_*` tools found. To wire up the project MCP:
  > 1. `npm run build` (rebuild `dist/index.js` if you changed source)
  > 2. Set whichever provider env vars you have keys for (e.g. `export HUNYUAN_API_KEY=sk-...`)
  > 3. Restart Claude Code so it reloads `.mcp.json`
  > 4. Re-run `/test-ask-experts`
  Stop here.

- **If you see at least one `ask_*` tool**: continue to Step 2. List the tools you found in a one-line summary.

### Step 2 — Probe each available expert with a canonical question

For each `ask_*` tool that is registered, call it **once** with the matching probe question from the table below. Use `response_language: "zh"` (default). Run the calls **in parallel** in a single message.

| Tool | Probe question |
|---|---|
| `ask_hunyuan` | `微信小程序 wx.login 拿到 code 后,如何 code2session 换 unionid?给出完整流程并标明对基础库版本的要求。` |
| `ask_qwen` | `阿里云 OSS 直传场景下,如何用 STS 临时凭证给浏览器/小程序生成 PostObject 表单签名?核心步骤即可,不必贴完整代码。` |
| `ask_doubao` | `飞书多维表格 (Bitable) 用开放平台 API 向某张数据表新增一条记录的请求示例,包含必要的 header 和 body。` |

For tools you don't have a probe for (e.g. user added a custom expert), skip them — note the skip in the report.

Pass each question via the `question` parameter. **Do not** add `context`. **Do not** retry on first failure.

### Step 3 — Score each response

For each call, classify the result as one of:

- **OK** — Returned a coherent, on-topic answer naming concrete API/SOP/concept names. The answer doesn't have to be perfect, just clearly drawing on domain knowledge.
- **WEAK** — Returned text but it's generic, hedged, or could've come from any model (no domain-specific signal).
- **ERROR** — Tool returned `isError: true` or an exception. Capture the error code (auth/timeout/rate_limit/server/empty/etc.) verbatim.

Be honest in your scoring — a confident-sounding but generic answer is **WEAK**, not OK. Look for: specific API method names, version-aware notes, mention of fields you wouldn't know without training data on that ecosystem.

### Step 4 — Final report

Output a markdown report with this structure:

```
## ask-experts-mcp validation — <YYYY-MM-DD>

### Registered tools
- ask_hunyuan, ask_qwen, ... (N total)

### Per-expert results
| Tool | Verdict | Notes |
|---|---|---|
| ask_hunyuan | OK | 给出了 wx.login → code2session → unionid 完整流程,提到基础库 ≥1.x.x |
| ask_qwen | WEAK | 只讲了 STS 通用概念,没提到 PostObject 表单字段细节 |
| ask_deepseek | ERROR (auth) | API Key 无效或无权限 (401) |

### Suggestions
- For the ERROR cases: <concrete next step, e.g. "DEEPSEEK_API_KEY 看起来无效,确认 Key 状态后重启 Claude Code">
- For WEAK cases: <suggest tightening trigger_keywords or trying a different model name>
- For OK cases: no action needed.
```

Keep the report concise — the user wants signal, not a wall of text. Don't paste full responses; one short sentence summarizing each is enough.

### Step 5 — If everything is OK

Add a final line: `✅ ask-experts-mcp 在本项目下工作正常,N/N 专家通过验证。`

If anything was WEAK or ERROR, end with `⚠️ 见上方 Suggestions。`

## Notes

- This skill expects the MCP server's tool list to already be live. It does not restart Claude Code or rebuild the project.
- If `dist/index.js` is stale (you just edited `src/`), rebuild with `npm run build` and restart Claude Code before invoking this skill.
- The probe questions are intentionally narrow; broader routing-quality testing is out of scope here (that's the v0.3.0 `tests/routing/` test set).