跳到正文
cccskills
免费在 GitHub 公开

elicit

Extract tacit knowledge through non-obvious microquestions — things only the user knows that can't be found in code, docs, or research. Use when you're about to guess at intent, context, or constraints during SAFEWORD's understanding flow. Also use when user says 'ask me', 'what do you need to know', or when another skill (bdd, brainstorm, debug) needs user context before proceeding. Do NOT use for questions answerable by reading the codebase or searching the web.

中文简介正在准备中。当前显示原文说明。

查看安装方法

包含的文件(1)

  • SKILL.md3.7 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Elicit: Tacit Knowledge Extraction

Draw out what the user knows and you can't research. Then check the latest evidence. Then explore options together.

Iron Law: NEVER ASK A QUESTION YOU COULD ANSWER YOURSELF. Read the code, search the docs, check git history first. Only ask what's left.

When to Run

  1. Explicitly — user invokes /elicit
  2. From other skills — any skill can call "run /elicit" before a decision point (e.g. bdd before scenarios, brainstorm when narrowing, debug when symptoms are ambiguous)
  3. Proactively — when you're about to make an assumption only the user can confirm

Relationship to other skills

  • brainstorm widens the option space (divergent). elicit narrows your uncertainty about user intent (convergent). Use brainstorm when you don't know the options; use elicit when you don't know the user's priorities among options.
  • SAFEWORD understanding flow already does contribute-before-asking. elicit is the structured form for decision points where guessing would be costly.

Phase 1: Microquestions

Ask one question at a time. Multiple choice (3-5 options). Force yourself to pre-think the option space so the user reacts rather than generates.

What to ask about

  • Intent: Why this way and not another? What was tried and rejected?
  • Constraints: What's off-limits? What's coming soon that would change the answer?
  • Priorities: When two good options conflict, which value wins?
  • Audience: Who reads/uses this? What do they already know?
  • Omissions: Is something missing because it's not ready, not wanted, or not thought of yet?

Question format

Good:

This could live in (a) the onboarding flow, (b) the decision-making page, or (c) as a standalone guide. Where would someone look for it?

Bad:

Where do you think this should go?

The good version does the thinking. The bad version makes the user do it.

How many

Keep asking until one of:

  • Answers start repeating or converging
  • You have enough to distinguish between options in Phase 3
  • User says "enough" or "go"

Typical: 3-7 questions. Fewer for small scope, more for ambiguous scope.

Phase 2: Research

After elicitation, check the latest evidence on the decision at hand. Web-search for:

  • Meta-analyses or systematic reviews
  • Replicated findings with effect sizes
  • How leading organizations handle this
  • Boundary conditions and known limitations

Skip if the task is purely operational (no empirical claims involved). Defer if the calling skill has its own research phase — don't duplicate work.

Phase 3: Options

Present 2-3 options. Each option:

  • What: the approach, concretely
  • Why it's good: what it gets right
  • What it costs: complexity, length, tradeoff
  • Evidence: what supports it (from Phase 2, if applicable)

For small scope (patch/task): just do it — skip the proposal, apply the best option directly. For larger scope (feature/policy): present options, let the user pick.

From Other Skills

When called from another skill, the elicitation results feed directly into the calling skill's next phase. No separate artifact — the conversation is the artifact.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

audit

免费

Run comprehensive code audit for architecture, dead code, and test quality. Use when reviewing overall codebase health, checking for architectural violations, or before marking a feature complete.

中文简介正在准备中。当前显示原文说明。

TheMostlyGreat/mythos192026年6月14日 更新

bdd

免费

Behavior-first feature development — use when building new capabilities, continuing feature work, or when work introduces new state or multiple user flows. Discovers desired behavior through examples and scenarios before implementation. Do NOT use for bug fixes, typos, or small isolated changes.

中文简介正在准备中。当前显示原文说明。

TheMostlyGreat/mythos192026年6月14日 更新

Use when the user wants to explore options, weigh approaches, or think through uncertainty before committing to a direction. Collaborative brainstorming and rubber ducking — divergence-first thinking partner.

中文简介正在准备中。当前显示原文说明。

TheMostlyGreat/mythos192026年6月14日 更新

Kill zombie dev servers and test processes. Use when ports are blocked, processes are hanging, or test runners won't start.

中文简介正在准备中。当前显示原文说明。

TheMostlyGreat/mythos192026年6月14日 更新

debug

免费

Root cause debugging before fixes. Use when investigating bugs, diagnosing test failures, troubleshooting unexpected behavior, or when previous fix attempts failed. Enforces investigate-first discipline.

中文简介正在准备中。当前显示原文说明。

TheMostlyGreat/mythos192026年6月14日 更新

Explore and debate options with fresh documentation and research before committing. Use when facing a real decision with multiple plausible approaches — library/framework choice, architecture call, API or schema design, algorithm selection, or any communication / strategy call where being wrong has cost. Enumerates relevant research domains, looks up current docs and evidence-based methods, weighs options on correctness and elegance, resists bloat. Do NOT use for divergent ideation (brainstorm), extracting user intent (elicit), or reviewing already-written code (quality-review).

中文简介正在准备中。当前显示原文说明。

TheMostlyGreat/mythos192026年6月14日 更新

查看 TheMostlyGreat 的全部技能

报告此技能的问题