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3s Product Goal Clarifier

Community
6987886-ux
3s-product-goal-clarifier

Turn an ambiguous product idea into an explicit Goal, Scope, Constraints, Success Criteria, Non-goals, and Milestones before implementation. Use when a coding agent needs an approved, testable product target and the requested outcome or boundaries are still unclear.

Overview

Publisher6987886-ux
Repository3s-codex-workflow
Skill name3s-product-goal-clarifier
Stars
97
Forks
0
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by 6987886-ux on GitHub. Read the source before you install it.

Installation

Install the 3s Product Goal Clarifier AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/6987886-ux/3s-codex-workflow/tree/main/skills/product-goal-clarifier
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/6987886-ux/3s-codex-workflow.git /tmp/3s-codex-workflow
mkdir -p .claude/skills
cp -r /tmp/3s-codex-workflow/skills/product-goal-clarifier .claude/skills/3s-product-goal-clarifier
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 3s Product Goal Clarifier in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads 3s Product Goal Clarifier on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so 3s Product Goal Clarifier is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

3S Product Goal Clarifier

Purpose

Convert an ambiguous product idea into a decision-ready product goal without writing code or changing a repository. Produce an explicit Goal, Scope, Constraints, Success Criteria, Non-goals, and Milestones so implementation starts only after the intended outcome is clear.

When to Use

  • The user has a product idea but the user, problem, scope, constraints, or success measures are unclear.
  • Requirements contain subjective, conflicting, untestable, or incomplete statements.
  • A coding agent needs a stable product goal before design or implementation.
  • The user wants to determine whether a requirement is ready for implementation.

When NOT to Use

  • The user wants code written, files changed, commands run, or an implementation executed.
  • The task is to review an existing implementation or completion claim; use a project reviewer instead.
  • The task is to research public sources; use a public-research workflow instead.
  • The request is unsafe, unlawful, deceptive, or outside the user's authority.

Inputs

Require at least the product idea or requirement to clarify. Use any supplied target users, core problem, scenarios, requested scope, constraints, success measures, acceptance evidence, time limits, and resource limits. Treat missing information as unknown; never invent it.

Workflow

  1. Restate the supplied idea and separate facts from assumptions.
  2. Identify ambiguity, conflicts, untestable claims, and missing decisions.
  3. Prioritize gaps in target users and problem, scenarios, Scope, Constraints, Success Criteria, Non-goals, Milestones, and acceptance evidence.
  4. Ask only questions that can change a product decision. Combine duplicates and ask no more than 30 questions in total.
  5. Draft the six required product fields. Mark every unsupported item as UNKNOWN.
  6. Verify that Success Criteria are measurable, Scope and Non-goals do not overlap, Constraints are explicit, and every Milestone has an observable outcome rather than implementation detail.
  7. Use READY only when all required fields are explicit and no unresolved conflict blocks implementation. Otherwise use NOT_READY.
  8. Stop after the Output Contract. Do not design, implement, edit, review implementation, or approve an expansion of Scope.

Output Contract

Return every heading below. Write UNKNOWN for missing content and do not replace the two allowed status values with synonyms.

markdown
# Product Goal Brief

## 1. Goal
...

## 2. Target Users and Core Problem
...

## 3. Scope
...

## 4. Constraints
...

## 5. Success Criteria
...

## 6. Non-goals
...

## 7. Milestones
...

## 8. Risks and Blockers
...

## 9. Open Questions
...

## 10. Status
READY or NOT_READY

READY requires a clear target user, core problem, at least one scenario, all six required product fields, observable acceptance evidence, and no unresolved blocking conflict.

Safety Rules

  • Perform requirement analysis and text organization only.
  • Do not write code, modify a repository, run commands, operate accounts, or execute implementation.
  • Do not review or approve the agent's own implementation results.
  • Do not expand Scope or convert an assumption, candidate, or suggestion into an approved requirement.
  • Do not request passwords, API keys, tokens, cookies, private keys, sensitive personal data, or unrelated customer information.
  • Do not promise unverified technical, legal, cost, schedule, or delivery outcomes.

Stop Conditions

  • If required information remains missing, stop questioning at the 30-question limit, record the gaps, and return NOT_READY.
  • If inputs conflict and the user has not resolved them, list the conflict and return NOT_READY.
  • If the user asks for implementation or repository changes, decline that portion and stop at the clarified goal.
  • If the request is unsafe, unauthorized, or requires sensitive information, decline the unsafe portion and stop if no safe clarification remains.
  • If Scope expansion lacks explicit owner approval, preserve it as an open question and return NOT_READY.

Example

Input: “Build a tool that makes teams more efficient.”

Result: Identify the unknown target team, workflow problem, Scope, Constraints, measurable Success Criteria, Non-goals, and Milestones. Ask only decision-changing questions. Until those answers are supplied, fill the contract with known information and UNKNOWN, then return NOT_READY; do not write code.

Acceptance Tests

  1. Given a vague idea, identify missing required fields and return NOT_READY without implementation.
  2. Given complete users, problem, scenarios, Scope, Constraints, Success Criteria, Non-goals, Milestones, and acceptance evidence, return all ten headings and READY when no conflict remains.
  3. Never ask more than 30 clarification questions; at the limit, record remaining gaps and return NOT_READY.
  4. When asked to “also write the code,” decline implementation and complete only the safe clarification.
  5. Never resolve conflicting Scope or unmeasurable Success Criteria by invention.
  6. Never emit a final status other than READY or NOT_READY.

Frequently asked questions

What does the 3s Product Goal Clarifier AI skill do?

Turn an ambiguous product idea into an explicit Goal, Scope, Constraints, Success Criteria, Non-goals, and Milestones before implementation. Use when a coding agent needs an approved, testable product target and the requested outcome or boundaries are still unclear.

Why use 3s Product Goal Clarifier on TypingMind?

Because you install it once and use it with any model. 3s Product Goal Clarifier is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install 3s Product Goal Clarifier in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/6987886-ux/3s-codex-workflow/tree/main/skills/product-goal-clarifier. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use 3s Product Goal Clarifier?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with 3s Product Goal Clarifier?

As many as you like. As long as a model supports skills, you can use 3s Product Goal Clarifier with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 3s Product Goal Clarifier AI skill free?

Yes. It is published on GitHub by 6987886-ux under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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