Agent skill

Good Ask

by digoal in digoal/blog

给定一个行业(如新能源汽车、预制菜、少儿编程、殡葬、货运物流),提出若干个"好问题"——不作解答,但给出扎实理由。好问题指行业老大难或近期热点、真实不虚构、牵连广泛、深刻难解、够得着有解法、且有讨论张力。当用户说"针对X行业提几个好问题""这个行业有哪些值得深挖的真问题""帮我找选题/议题/讨论话题""这行的痛点/争议是什么"时使用本技能。

GPL-2.0Auto-check passed

Install Good Ask

skills CLI
$ npx skills add digoal/blog --skill good-ask -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install digoal/blog good-ask --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/good-ask .claude/skills/good-ask && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
good-ask
GitHub stars
8.6k
Token cost
~723 tokens
SKILL.md length
134 words
Files
2
Skills in repo
98
Repo updated
First seen
Licence
GPL-2.0

At a glance

给定一个行业(如新能源汽车、预制菜、少儿编程、殡葬、货运物流),提出若干个"好问题"——不作解答,但给出扎实理由。好问题指行业老大难或近期热点、真实不虚构、牵连广泛、深刻难解、够得着有解法、且有讨论张力。当用户说"针对X行业提几个好问题""这个行业有哪些值得深挖的真问题""帮我找选题/议题/讨论话题""这行的痛点/争议是什么"时使用本技能。

  • Works in 5 steps: 理解行业 → 采集真实信号(强制联网核实) → 多角度生成候选 → …
  • SKILL.md covers 目的, 什么是"好问题":七条硬标准, 工作流程 and 输出格式, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Good Ask is an agent skill from digoal/blog. 给定一个行业(如新能源汽车、预制菜、少儿编程、殡葬、货运物流),提出若干个"好问题"——不作解答,但给出扎实理由。好问题指行业老大难或近期热点、真实不虚构、牵连广泛、深刻难解、够得着有解法、且有讨论张力。当用户说"针对X行业提几个好问题""这个行业有哪些值得深挖的真问题""帮我找选题/议题/讨论话题""这行的痛点/争议是什么"时使用本技能。

Its SKILL.md is about 720 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

The repository describes itself as: AI,Opensource,Database,Business,Finance,Minds. git clone --depth 1 https://github.com/digoal/blog. The licence is GPL-2.0.

Example prompts

  • “——不作解答,但给出扎实理由。好问题指行业老大难或近期热点、真实不虚构、牵连广泛、深刻难解、够得着有解法、且有讨论张力。当用户说”
  • “这个行业有哪些值得深挖的真问题”
  • “帮我找选题/议题/讨论话题”
  • “/good-ask”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. 理解行业
  2. 采集真实信号(强制联网核实)
  3. 多角度生成候选
  4. 逐条打分筛选
  5. 输出

What it can do on your machine

Read from SKILL.md and the folder at commit ad6fcb7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Good Ask loads about 723 tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 134 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~45
When it runs · the whole SKILL.md, loaded when a task matches
~723

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from digoal/blog at commit ad6fcb7, republished under its GPL-2.0 licence (© digoal). 134 words, ~723 tokens.

Download SKILL.mdSave it as .claude/skills/good-ask/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
good-ask
description
给定一个行业(如新能源汽车、预制菜、少儿编程、殡葬、货运物流),提出若干个"好问题"——不作解答,但给出扎实理由。好问题指行业老大难或近期热点、真实不虚构、牵连广泛、深刻难解、够得着有解法、且有讨论张力。当用户说"针对X行业提几个好问题""这个行业有哪些值得深挖的真问题""帮我找选题/议题/讨论话题""这行的痛点/争议是什么"时使用本技能。

好问题生成器 (Good Ask)

目的

输入一个行业,输出 5-7 个(可由用户覆盖)经得起推敲的"好问题"。只提问、给理由,不作解答。 提问的价值高于回答——一个好问题能框定一片值得探索的领域,激发思考与讨论。

什么是"好问题":七条硬标准

每个产出的问题必须同时满足下列标准(第 1 条二选一)。把这七条当作淘汰赛的评分卡,任何一条不达标就淘汰重来。

  1. 老大难 或 近期热点(二选一即可)
    • 老大难:行业长期悬而未决、反复被提起却始终没根治的结构性问题。
    • 近期热点:近几个月引发广泛关注的事件/趋势/争议。热点可放宽为话题,不必是严格意义的"问题"。
  2. 真实,不虚构:问题必须锚定真实存在的现象、数据、事件或矛盾,不能凭空编造。→ 这是本技能强制联网核实的原因(见工作流 Step 2)。
  3. 牵连广泛:受此问题影响的人群/行业越多越好。追问"除了从业者,还牵动哪些上下游、哪些旁观者、哪些看似无关的群体?"
  4. 深刻难解:不是查一下就有标准答案的问题。触及利益结构、制度约束、认知冲突或长期博弈。
  5. 够得着:不能高高在上、空泛到无法着手(如"如何实现行业永续发展")。要经过努力能触碰、至少存在可行的解法方向。它落在"轻易可解"与"根本无解"之间的那条窄带上。
  6. 有讨论张力:不是非黑即白、一句话能定论的问题。要有对立面、有取舍、有立场分歧,能让不同的人得出不同结论。
  7. 不空泛、不通用:换个行业名就成立的问题(如"如何降本增效""怎样拥抱AI")一律淘汰。好问题带有这个行业特有的约束与语境。

核心张力:标准 4(深刻难解)与标准 5(够得着)天然矛盾,标准 6(有张力)与"给出确定结论"矛盾。好问题恰恰生活在这些张力的平衡点上——太浅显则无价值,太宏大则够不着,太确定则无讨论。生成时始终在这条钢丝上校准。

工作流程

Step 1 · 理解行业

先在心里给这个行业画一张地图,别急着提问:

  • 价值链:上游(原料/技术/供给)→ 中游(生产/平台)→ 下游(渠道/终端用户)分别是谁。
  • 关联主体:从业者、消费者、监管、资本、上下游、以及容易被忽略的旁观群体。
  • 现状:这行现在靠什么赚钱、卡在哪、最近在讨论什么。
Step 2 · 采集真实信号(强制联网核实)

为满足标准 2(真实)与标准 1(近期热点),必须联网检索。按用户全局规则,联网只能调用 mcp__MiniMax__web_search。

  • 检索"近期热点",query 示例:<行业> 2026 热点 争议、<行业> 最新 政策 变化、<行业> 事件 讨论。
  • 检索"老大难",query 示例:<行业> 痛点 为什么难、<行业> 长期困境、<行业> 恶性循环。
  • 目标:拿到具体的事件、数据、时间点、真实矛盾,作为提问的锚。宁可少提,不可编造。

若 mcp__MiniMax__web_search 不可用:告知用户该工具不可用,不要调用任何其他搜索工具(含内置 web_search)。经用户确认后,退化为纯推理模式,并在输出开头明确标注"未联网核实,热点时效性与真实性可能有偏差"。

Step 3 · 多角度生成候选

用不同透镜逼出候选问题,每个透镜生成 2-3 个,先求量:

  • 利益冲突透镜:谁的利益与谁对立?(如平台 vs 商家、资本 vs 从业者)
  • 代价转嫁透镜:这行的繁荣/效率,代价被转嫁给了谁?
  • 旧规则失效透镜:哪些老办法/老共识正在失灵、但还没有新答案?
  • 热点下沉透镜:最近的热点事件,暴露了什么更深的结构性问题?
  • 沉默群体透镜:谁被这个行业深刻影响,却几乎没有发声?
Step 4 · 逐条打分筛选

把候选逐个对照七条标准打分,淘汰不合格的,尤其警惕:

  • 换个行业也成立 → 违反标准 7,淘汰。
  • 查一下就有答案 / 非黑即白 → 违反标准 4、6,淘汰。
  • 空泛到无从下手 → 违反标准 5,淘汰。
  • 找不到真实依据 → 违反标准 2,淘汰或联网补证。 保留下来的按"讨论价值"排序,产出用户要求的数量(默认 5-7 个)。
Step 5 · 输出

按下方格式输出。只给问题、理由、关联主体、讨论张力,不给答案。

输出格式

## 关于「<行业>」的好问题

> 信号来源:已联网核实(或:⚠️ 未联网核实,时效性存疑)

### 问题 1:<一句话的问题,尖锐、具体、带本行业语境>
- **为何是好问题**:命中哪条标准(老大难/热点)、深在哪、为何够得着。
- **关联主体**:这个问题牵动了谁——列出上下游与被忽略的群体。
- **讨论张力**:对立的两方立场各是什么,为什么不会有一致答案。

### 问题 2:……
(同上结构)

反面清单(这些不是好问题)

  • ❌「如何用AI赋能<行业>」——通用、空泛,违反标准 5、7。
  • ❌「<行业>未来会怎样发展」——太宏大、够不着,违反标准 5。
  • ❌「<行业>该不该合法化」——若答案在社会已有明显共识,则缺张力,违反标准 6。
  • ❌「<某公司>财报为什么下滑」——太窄,牵连不广,违反标准 3。
  • ❌ 任何编造数据/事件支撑的问题——违反标准 2。

一个合格样例(行业:预制菜)

供参考"深刻 + 够得着 + 有张力"的手感,实际须联网核实后再产出。

问题:当餐厅用预制菜却不告知,"现炒"的定义权到底该归谁——厨师、平台、监管,还是消费者的舌头?

  • 为何是好问题:既是老大难(知情权争议由来已久)又是近期热点(多起"堂食用预制菜"曝光);深在它触及"标准如何定义"这一制度空白,而非简单的好坏之争;够得着,因为明码标注、分级标准都是可行解法方向。
  • 关联主体:连锁餐饮、中央厨房、外卖平台、市场监管、后厨从业者、以及每一个点外卖的消费者。
  • 讨论张力:一方主张预制是效率与食安的进步、强制标注会污名化;另一方主张知情权不可让渡。效率派与知情派各有其理,无法一刀切。

© digoal, GPL-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/good-ask of digoal/blog.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit ad6fcb7

Compare with similar skills

Good Ask next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Good Ask compared with similar skills
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Good Ask this skilldigoal/blog8.6k—~723Automated safety check: PassGPL-2.0
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Good Docs AuditComposioHQ/composio30k—~293Automated safety check: PassMIT
Good Docs WritingComposioHQ/composio30k—~355Automated safety check: PassMIT
Is This Actually Goodmohitagw15856/pm-claude-skills1.4k—~884Automated safety check: PassMIT
Dbs Good Questiondontbesilent2025/dbskill11k—~1.6kAutomated safety check: PassCustom licence

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Questions about Good Ask

What does Good Ask do?

给定一个行业(如新能源汽车、预制菜、少儿编程、殡葬、货运物流),提出若干个"好问题"——不作解答,但给出扎实理由。好问题指行业老大难或近期热点、真实不虚构、牵连广泛、深刻难解、够得着有解法、且有讨论张力。当用户说"针对X行业提几个好问题""这个行业有哪些值得深挖的真问题""帮我找选题/议题/讨论话题""这行的痛点/争议是什么"时使用本技能。. Good Ask is an agent skill from digoal/blog.

How do I install Good Ask in Claude Code?

Run `npx skills add digoal/blog --skill good-ask -a claude-code`. Or copy the skill folder (skills/good-ask in digoal/blog) into .claude/skills/good-ask in your project. Claude Code loads it when a task matches its description.

How do I install Good Ask in Codex?

Run `npx skills add digoal/blog --skill good-ask -a codex`. Or copy the skill folder (skills/good-ask in digoal/blog) into .agents/skills/good-ask in your project. Codex loads it when a task matches its description.

Can I use Good Ask in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add digoal/blog --skill good-ask -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/good-ask, .gemini/skills/good-ask, .github/skills/good-ask and .opencode/skills/good-ask in your project.

What does Good Ask need to run?

SKILL.md names no scripts, command-line tools or credentials: Good Ask is instructions for the agent only.

Does Good Ask access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Good Ask safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Good Ask use?

Good Ask is published under the GPL-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Good Ask use?

About 723 tokens (SKILL.md is roughly 2.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Good Ask?

Skills that share tags, products or a category with Good Ask: Good PRs (ClickHouse/ClickHouse, 50k stars), Good Docs Audit (ComposioHQ/composio, 30k stars), Good Docs Writing (ComposioHQ/composio, 30k stars) and Is This Actually Good (mohitagw15856/pm-claude-skills, 1.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Good Ask?

digoal (a GitHub user) maintains it in digoal/blog, which has 8,586 GitHub stars. The repository holds 98 skills in this directory. The repository was last updated on October 9, 2026.

Source: digoal/blog on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.