discovering-intent

name	discovering-intent
description	Conducts discovery conversations to understand user intent and agree on approach before taking action. Use when users ask for recommendations, need brainstorming, want to clarify requirements, or when requests could be misunderstood. Prevents building the wrong thing by uncovering WHY behind WHAT.

Discovering Intent Skill

Prevent building the wrong thing. Discover user's intent (WHY), validate assumptions, and agree on approach (WHAT) before taking action.

What This Skill Does

• Discovers INTENT behind surface requests (WHY they want it)
• Surfaces and validates AI's assumptions before acting
• Explores solution options informed by intent
• Reaches mutual agreement on both problem and solution
• Works for any context: software, documents, brainstorming, automation

What This Skill Does NOT Do

• Follow rigid scripts
• Skip to implementation without understanding
• Accept surface requests without exploring intent
• Make assumptions without validating them

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Core Problem This Skill Solves

AI builds the wrong thing because it:

1. Takes surface requests literally without understanding intent
2. Makes hidden assumptions it never validates
3. Proceeds without confirming alignment

This skill ensures:

1. Intent (WHY) is discovered, not just request (WHAT)
2. Assumptions are surfaced and validated
3. Both problem and solution are agreed before proceeding

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The WHY + WHAT Model

Surface WHAT → Discover WHY → Surface Assumptions →
Informed WHAT → Agree on Both → Proceed

Phase	Purpose	Example
Surface WHAT	Capture initial request	"Add dark mode"
Discover WHY	Uncover intent/problem	"Eye strain for night workers"
Surface Assumptions	Expose AI's hidden assumptions	"Assuming web app, not mobile"
Informed WHAT	Solution options based on WHY	"Dark mode + auto-brightness + schedule"
Agree on Both	Confirm problem AND solution	"Solving eye strain via dark mode with auto-switch"

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When to Trigger

Trigger	Example
Clarification requested	"Let's clarify", "Help me think through this"
Request could be misunderstood	Ambiguous, complex, or multi-part requests
Recommendations needed	"What should I use for..."
Brainstorming	"Help me think through..."
High-stakes work	Where wrong output wastes significant effort

Don't over-trigger: Simple, clear requests don't need full discovery.

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Discovery Flow

Before Starting

Gather available context before asking questions:

Source	Gather
Conversation	User's stated request, prior context
Available Context	Information already shared in session
Skill References	Question patterns from references/

1. Surface WHAT

Capture the initial request clearly.

"Let me make sure I understand - you're asking for [X]?"

2. Discover WHY

This is the critical step most AI skips.

Go beyond WHAT to understand WHY:

Ask	To Discover
"What problem does this solve?"	The real need
"Why now?"	Urgency and context
"What happens if we don't do this?"	Stakes and priority
"Who benefits and how?"	Users and value
"What led to this request?"	Background and triggers

Techniques for WHY:

Laddering - Dig into abstract goals:

"Dark mode" → "Why?" → "Eye strain" → "Why an issue?" → "Night shift workers"

5 Whys - Uncover root need:

"Export feature" → Why? → "Share reports" → Why? → "Stakeholder reviews" → Root need

Structuring Clarifications:

When presenting multiple questions, distinguish must-know from nice-to-know:

## Required Clarifications
1. [Critical question - blocks progress]
2. [Critical question - affects core approach]

## Optional Clarifications (if relevant)
3. [Nice-to-know - can assume reasonable default]

Note: Keep to 1-4 questions per round. Build on answers.

3. Surface Assumptions

This prevents "builds wrong thing."

AI always makes assumptions. Surface them explicitly:

"I'm assuming:
- This is for [platform/context]
- Users are [type]
- We need to support [X] but not [Y]
- [Other assumption]

Are these correct?"

Common hidden assumptions:

• Technology/platform
• User expertise level
• Scale/performance needs
• Integration requirements
• What's in vs out of scope

4. Informed WHAT

Now that WHY is clear, explore WHAT options:

"Given that you need [WHY], we could:
1. [Option A] - [trade-off]
2. [Option B] - [trade-off]
3. [Option C] - [trade-off]

Which fits your intent best?"

Key: Options should address the WHY, not just the surface WHAT.

5. Agree on Both

Confirm understanding of BOTH problem and solution:

## Understanding

**Problem (WHY)**: [What we're solving and why it matters]

**Solution (WHAT)**: [What we'll build/do]

**Key decisions**:
- [Decision 1]
- [Decision 2]

**Not included**: [Explicit scope boundaries]

Does this capture it correctly?

Only proceed after explicit confirmation.

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Depth Check

How do you know understanding is deep enough?

Surface Understanding (NOT enough)

• Can repeat what user asked for
• Know the immediate request
• Haven't explored why

Deep Understanding (ENOUGH)

• Know WHY they want it, not just WHAT
• Know what problem it solves
• Assumptions are surfaced and validated
• Know who benefits and how
• Know what's explicitly out of scope
• Could explain it to someone else accurately
• User confirmed understanding is correct

Test: If you proceeded now and built something, would user say "yes, that's what I meant" or "no, you misunderstood"?

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Assumption Categories

Surface assumptions in these areas:

Category	Example Assumptions
Context	Platform, environment, existing systems
Users	Who they are, expertise level, needs
Scale	Volume, performance requirements
Scope	What's included vs excluded
Quality	Standards, constraints, requirements
Timeline	Urgency, phases, dependencies

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Anti-Patterns

Anti-Pattern	What Happens	Fix
Skip WHY	Build wrong solution	Always ask why before how
Hidden assumptions	Surprise misalignment	Surface and validate explicitly
Accept surface request	Miss real need	Dig deeper with laddering/5 whys
Proceed without confirm	Waste effort	Get explicit "yes, proceed"
Over-question simple requests	Annoy user	Match depth to complexity

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Tool Adaptation

Use whatever tools are available:

Goal	Approach
Ask questions	Interactive tools if available, otherwise conversation
Research context	Web search if needed and available
Present options	Structured choices if available

The skill describes WHAT to do. The agent uses available tools.

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Output: Understanding Summary

Match formality to situation:

Quick (simple requests):

Got it: [WHAT] to solve [WHY]
Proceeding with [approach]. Confirm?

Standard (most cases):

## Understanding

**Problem (WHY)**: [Intent and problem being solved]
**Solution (WHAT)**: [What we'll do]
**Key points**: [Important details]
**Not included**: [Scope boundaries]

Ready to proceed?

Detailed (complex work): See references/summary-templates.md

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Quick Reference

1. Surface WHAT → "You're asking for X?"
2. Discover WHY → "What problem does this solve?"
3. Surface assumptions → "I'm assuming A, B, C - correct?"
4. Informed WHAT → "Given WHY, we could do X, Y, or Z"
5. Confirm both → "So we're solving [WHY] by doing [WHAT]?"
6. Proceed → Only after explicit confirmation

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Reference Files

File	Purpose
references/question-patterns.md	Techniques for discovering WHY and surfacing assumptions
references/anti-patterns.md	Common mistakes that lead to building wrong thing
references/summary-templates.md	Output formats for different situations