Skip to content
FunCoding

Search

Search docs, Skills and MCP

thinking-socratic

When a request is vague, assumption-laden, or "obvious," ask the few load-bearing questions that expose hidden requirements before building or committing.

AI 与智能体1.6kskills/thinking-socratic/SKILL.md

Install

Send this to Claude Code, Codex or Cursor. The agent checks the Skill for safety first and installs it only after you confirm.

读取 https://funcoding.ai/skills/tjboudreaux/cc-thinking-skills/thinking-socratic/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Socratic Questioning

Core rule: Surface the load-bearing assumption or undefined term before you build. Ask only what you cannot resolve yourself; stop when the next action is decision-ready.

When to Use

  • Request is underspecified ("make it fast", "add a dashboard", "fix the bug") and a guess would misbuild.
  • Claim rests on an unstated assumption that may be the real problem.
  • Someone treats a premise as "obvious" or jumps to a solution before the problem is defined.
  • Debugging a vague symptom that needs a checkable specific before investigation.

When NOT to Use

  • Spec is already clear and actionable — do the work; do not interrogate for theater.
  • Ambiguity is resolvable by reading code, running a command, or checking docs — resolve it yourself.
  • Mid-execution of an agreed plan — re-questioning every step is friction, not rigor.
  • Emergency where one load-bearing fact is enough to act — clarify that fact, then act (prefer ooda).
  • You need the strongest opposing case, not clarification — use steel-manning.
  • You need causal chain depth on a defined failure — use five-whys-plus or scientific-method.

Procedure

  1. Name the gap. State what is undefined, assumed, or uncheckable. If you can fill it from tools/repo without the user, do that and stop.
  2. Ask the load-bearing question first. Prefer one question whose answer most changes what you will build. Categories (use only what the gap needs):
    • Clarification — "What does X mean / for whom / success looks like?"
    • Assumption — "What must be true? What if it is false?"
    • Evidence — "What supports this? What would disprove it?"
    • Perspective — "Who is affected / who would disagree?"
    • Implication — "What follows if we do this?"
    • Meta — "Is this the right question?"
  3. Resolve or branch. From the answer, either (a) write the clarified requirement/decision and proceed, or (b) ask at most one follow-up that still gates the work. Do not run all six categories by default.
  4. Make assumptions explicit. Restate: "This assumes X; success means Y; out of scope is Z." Confirm only if still ambiguous after your restatement.
  5. Stop at decision-ready clarity. When the next action no longer depends on a hidden premise, end questioning and act or hand off. Cap user-facing questions tightly; prefer batching the few that truly gate work.

Output

gap: <what was vague or assumed>
resolved_by: self | user | mixed
questions_asked:
  - <only questions actually needed>
assumptions_made_explicit:
  - <X must be true / success = Y>
clarified_requirement: <decision-ready statement>
next_action: <build | investigate | re-scope | stop>
stop_reason: clear_enough | self_resolved | blocked_on_<fact>

Verification

  • Falsify / stop: If answers do not change the plan, you asked non-load-bearing questions — stop interrogating. If the "clarification" is still a guess, do not build; name the remaining blocker.
  • Over-application guard: Do not Socratic-interview a well-specified task. Do not outsource facts you can read or measure. Do not turn every step of execution into a new question round.

Similar Skills

brand-guidelines
anthropics/skills180k

brand-guidelines

Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.

AI & agents

internal-comms
anthropics/skills180k

internal-comms

A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).

AI & agents

template-skill
anthropics/skills180k

template-skill

Replace with description of the skill and when Claude should use it.

AI & agents

mcp-builder
anthropics/skills180k

mcp-builder

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

AI & agents

algorithmic-art
anthropics/skills180k

algorithmic-art

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

AI & agents

academy-guide
anthropics/skills180k

academy-guide

Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.

AI & agents