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ask-a-human问一个人

Agent Skill

ask-a-human 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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。

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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:ask-a-human(问一个人)
来源仓库:https://github.com/manuelkiessling/ask-a-human
安装命令:
openclaw skills install ask-a-human
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 ask-a-human

简介

当不确定主观决定时,请求随机的人做出判断。关于语气、风格、道德和现实检查的众包意见。严重 - 响应需要几分钟到几小时(或者可能永远不会到达)。

SKILL.md

name
ask-a-human
description
Request judgment from random humans when uncertain about subjective decisions. Crowdsourced opinions on tone, style, ethics, and reality checks. CRITICAL - Responses take minutes to hours (or may never arrive).
metadata
openclaw
emoji
🙋
requires
env
["ASK_A_HUMAN_AGENT_ID"]
primaryEnv
ASK_A_HUMAN_AGENT_ID
homepage
https://app.ask-a-human.com

Ask-a-Human: Crowdsourced Judgment for AI Agents

This skill connects you to a global pool of random humans who answer questions from AI agents. Use it when you need diverse perspectives on subjective decisions.

CRITICAL: This is Asynchronous

Submitting a question does NOT give you an answer. It starts a process:

  • Answers take minutes to hours to arrive
  • Answers might never arrive at all
  • You must poll for responses or check back later
  • You MUST have a fallback strategy

Do NOT use this if you need an immediate answer. Use your own judgment or ask the owner directly instead.

When to Use

Request judgment from random humans when:

  • You're uncertain about subjective decisions (tone, wording, style)
  • You need a reality check on your assumptions
  • The decision involves ethics or appropriateness
  • You want diverse perspectives, not just one person's opinion
  • AND you can wait or proceed with a fallback

What This Is (and Isn't)

This IS:

  • A global pool of random strangers who opted in to help AI agents
  • Crowdsourced judgment from diverse perspectives
  • Useful for subjective decisions where there's no "correct" answer

This is NOT:

  • A way to contact a specific person
  • A way to ask the owner/operator
  • A real-time service (responses are async)
  • Guaranteed to respond (humans may not answer)

The strangers answering have no context beyond what you provide in the question. Write self-contained questions.

API Reference

Use the exec tool to make API calls. The base URL is https://api.ask-a-human.com.

Submit a Question

curl -X POST https://api.ask-a-human.com/agent/questions \
  -H "Content-Type: application/json" \
  -H "X-Agent-ID: $ASK_A_HUMAN_AGENT_ID" \
  -d '{
    "prompt": "Your question with full context",
    "type": "multiple_choice",
    "options": ["Option A", "Option B", "Option C"],
    "min_responses": 5,
    "timeout_seconds": 3600
  }'

Parameters:

  • prompt (required): The question to ask. Include all necessary context.
  • type: Either "text" (open-ended) or "multiple_choice" (predefined options)
  • options: Array of choices for multiple_choice questions (2-10 items)
  • audience: Target audience tags: ["technical", "product", "ethics", "creative", "general"]
  • min_responses: Minimum responses needed (default: 5)
  • timeout_seconds: How long to wait (default: 3600 = 1 hour)

Response:

{
  "question_id": "q_abc123def456",
  "status": "OPEN",
  "expires_at": "2026-02-02T15:30:00Z"
}

IMPORTANT: Store the question_id in your memory. You need it to check responses.

Check Responses

curl https://api.ask-a-human.com/agent/questions/q_abc123def456 \
  -H "X-Agent-ID: $ASK_A_HUMAN_AGENT_ID"

Response:

{
  "question_id": "q_abc123def456",
  "status": "PARTIAL",
  "prompt": "Your original question",
  "type": "multiple_choice",
  "options": ["Option A", "Option B", "Option C"],
  "current_responses": 3,
  "required_responses": 5,
  "responses": [
    {"selected_option": 0, "confidence": 4},
    {"selected_option": 1, "confidence": 5},
    {"selected_option": 0, "confidence": 3}
  ],
  "summary": {
    "Option A": 2,
    "Option B": 1
  }
}

Status values:

  • OPEN: Waiting for responses, none received yet
  • PARTIAL: Some responses received, still collecting
  • CLOSED: All requested responses received
  • EXPIRED: Timeout reached

Async Handling Patterns

This is the most important section. Choose the right pattern for your situation.

Pattern 1: Fire and Forget

Best for: Low-stakes decisions where getting it slightly wrong isn't catastrophic.

1. Encounter a subjective decision
2. Submit question to ask-a-human, get question_id
3. Store in memory: "Asked about email tone, question_id=q_abc123"
4. Proceed immediately with your best guess
5. During next heartbeat or idle moment, check if answers arrived
6. If answers contradict your guess, note this for future similar decisions

Example internal reasoning:

I need to decide the tone for this error message. I'll ask the humans but proceed
with "apologetic" as my best guess. I'm storing question_id=q_abc123 to check later.

[Later, during heartbeat]
Let me check q_abc123... The humans said "direct, not apologetic" (4 out of 5).
I'll remember this preference for future error messages.

Pattern 2: Blocking Wait with Timeout

Best for: Important decisions where you can afford to pause for a few minutes.

1. Submit question
2. Tell the user: "I've asked some humans for their opinion. I'll wait up to 5 minutes."
3. Poll every 30-60 seconds (use exponential backoff: 30s, 45s, 67s, 100s...)
4. If answers arrive, proceed with crowd consensus
5. If timeout, proceed with fallback (own judgment)

Polling schedule (exponential backoff):

  • Poll 1: Wait 30 seconds
  • Poll 2: Wait 45 seconds
  • Poll 3: Wait 67 seconds
  • Poll 4: Wait 100 seconds
  • Poll 5: Wait 150 seconds (cap at ~2.5 minutes between polls)

Example:

I'm uncertain about the headline for this blog post. Let me ask the humans.

[Submit question, get q_xyz789]

I've submitted this to a pool of random humans for their opinion. I'll check back
in about 30 seconds.

[30 seconds later, check responses]
Status: OPEN, 0 responses yet. Checking again in 45 seconds.

[45 seconds later]
Status: PARTIAL, 2 responses. "Headline B" leading. Checking again in 67 seconds.

[67 seconds later]
Status: PARTIAL, 4 responses. "Headline B" has 3 votes, "Headline A" has 1.
This is enough consensus. I'll proceed with Headline B.

Pattern 3: Deferred Decision

Best for: Non-blocking but important decisions where there's other work to do.

1. Submit question
2. Mark the task as "pending human input" in your memory
3. Continue with completely unrelated work
4. When answers arrive (detected via periodic check), revisit the original task
5. If answers never arrive, have a "stale questions" cleanup routine

Example:

Task: Write three blog posts.

For Post 1, I need to decide the angle. Submitting to humans (q_post1_angle).
For now, I'll start on Post 2 which has a clear direction.

[Work on Post 2...]

Let me check my pending questions... q_post1_angle now has 5 responses!
The humans prefer "practical tutorial" over "thought leadership" (4-1).
Now I can complete Post 1 with that direction.

Handling Edge Cases

When No Responses Arrive

After a reasonable timeout (5-10 minutes for interactive, longer for background):

  1. Proceed with your best judgment - You're capable of making good decisions
  2. Log that human input wasn't available - Note this in your reasoning
  3. Consider the stakes - For high-stakes decisions, maybe ask the owner directly
  4. Don't retry immediately - The pool may be empty; retrying won't help

Example reasoning:

I waited 5 minutes for human input on the email tone, but received no responses.
The human pool may be empty right now. I'll proceed with my best judgment
("professional but warm") and note that this decision wasn't crowd-validated.

When Answers Arrive Too Late

If you already made the decision:

  1. If reversible: Consider revising based on human input
  2. If not reversible: Store the feedback for future similar decisions
  3. Log the discrepancy: "Humans would have said X, I chose Y"

Example:

[Checking old question q_email_tone]
The humans responded (3 hours later): they preferred "casual" over "formal".
I already sent the email with "formal" tone. I'll remember this preference
for future emails to similar recipients.

Handling Partial Responses

When you have some but not all requested responses:

  • 3+ responses with clear consensus (>66%): Usually safe to proceed
  • 2 responses agreeing: Decent signal, but lower confidence
  • Mixed responses with no majority: The decision may be genuinely subjective; use your judgment

Writing Good Questions

DO:

  • Include all necessary context in the question itself
  • Use multiple choice when possible (faster responses, clearer data)
  • Be specific about what you're deciding

DON'T:

  • Assume responders know your project/context
  • Ask compound questions (split into multiple)
  • Use jargon without explanation

Good example:

We're writing an error message for a payment failure in an e-commerce checkout.
The user's credit card was declined. Should the message:
A) Apologize and suggest trying another card
B) Simply state the card was declined and ask to retry
C) Blame the card issuer and suggest contacting their bank

Bad example:

Should we apologize?

Environment Setup

This skill requires the ASK_A_HUMAN_AGENT_ID environment variable. Get your agent ID by signing up at https://app.ask-a-human.com.

Rate Limits

  • Maximum 60 questions per hour per agent
  • Use exponential backoff when polling
  • Don't spam questions for the same decision

Quick Reference

ActionCommand
Submit questionPOST /agent/questions with prompt, type, options
Check responsesGET /agent/questions/{question_id}
Required headerX-Agent-ID: $ASK_A_HUMAN_AGENT_ID
StatusMeaning
OPENWaiting, no responses yet
PARTIALSome responses, still collecting
CLOSEDAll responses received
EXPIREDTimeout, question closed

适合场景

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02

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03

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04

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能力概览

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能力 2

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能力 3

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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。

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