Ask a Human Expert

Overview

Instant Expert sends a paid ask from the user's account to real professionals: executives, operators and domain experts it finds from a description, or one specific person the user names. Each ask is a question for a written or voice answer, or a 15 to 60 minute call. The person is paid only if they answer or book, and the user is charged only then. Use it for knowledge work (judgment and first-hand experience from specific people), not errands or physical tasks.

The agent drives Instant Expert's MCP tools. When they aren't connected, it calls the free test server with curl, so the whole flow can be tried with no account or card. Adapted from the official skill, which also bundles a small test-mode helper script: https://github.com/Instant-Expert/skills

When to Use This Skill

• Use when the answer needs a practitioner's experience rather than a web page: "How long did SOC 2 Type II take you?", "How do claims teams at mid-size insurers triage?"
• Use for customer discovery, user interviews, expert input, or a first conversation with a kind of buyer.
• Use when the user names someone to reach: "Jane Doe, VP of Sales at Acme", a LinkedIn URL or an email.
• Use when the user asks whether anyone answered an earlier ask.
• Do not use to find personal contact details, to get confidential or material non-public information, for physical tasks, or to message people the user hasn't approved.

How It Works

Step 1: Pick the mode

If the session already has the Instant Expert MCP tools (search_people, queue_requests, prepare_request_order and so on), call them directly. A result with "test_mode": true came from test mode; anything else is the user's live account.

Otherwise start a free 24-hour test sandbox. No account or card is needed, and each network can start 5 an hour, so reuse the token until it expires:

mkdir -p ~/.config/instant-expert
curl -sS -X POST https://instant.expert/api/sandbox -o ~/.config/instant-expert/sandbox.json

The saved JSON has token, expires_at and mcp_url. Call a tool by posting a JSON-RPC tools/call to the test server. It is stateless, so no initialize step is needed:

curl -sS https://instant.expert/mcp/test \
  -H "Authorization: Bearer $(sed -n 's/.*"token":"\([^"]*\)".*/\1/p' ~/.config/instant-expert/sandbox.json)" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"list_requests","arguments":{}}}'

The answer is in result.structuredContent (the same JSON is in result.content[0].text). result.isError: true means the tool rejected the call; read its message. Use "method":"tools/list" to see every tool and its arguments. An HTTP 401 means the sandbox expired, so start a new one.

Test mode has about 300 fictional people at fictional companies, so a niche search comes back with the closest fictional matches. Invitations are recorded instead of sent, the fictional people answer within seconds, and orders use a Stripe test card. Nothing reaches a real person or moves real money. Tell the user once that results are simulated.

Step 2: Choose who to ask

Tools that start work (search_people, import_people, queue_requests) return a job_id. Poll get_job, waiting poll_after_seconds between calls, until status is succeeded or failed. Give every new operation its own idempotency_key, and reuse a key only to retry the same call.

• A named person with a LinkedIn URL or email: skip searching and pass people to queue_requests, for example [{"linkedin_url": "https://www.linkedin.com/in/..."}].
• A named person with only a name and company: call import_people with people set to [{"name": "...", "company": "..."}], then get_search. If there's no match, ask the user for a LinkedIn URL or email.
• A kind of person: call search_people once with the whole request, including how many people and any exclusions, then read the list with get_search (page_size: 100).
• Only a goal ("we're building X, who should we talk to?"): call plan_outreach with a description, let the user pick an audience, then run its search_query through search_people.

Step 3: Draft the ask

Call queue_requests with search_id (plus person_profile_ids to keep a subset) or people, and:

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