/arn-spark-discover

name: arn-spark-discover
description: >-
  This skill should be used when the user says "discover", "product discovery",
  "arn discover", "help me define this product", "what should I build",
  "product concept", "define the product", "let's figure out what to build",
  "vision for this project", "shape this idea", "new project idea",
  "brainstorm this product", "starting from scratch", or wants to explore
  and structure a greenfield product idea through guided conversation. Produces a
  product-concept.md document capturing the product vision, core experience,
  target users, trust model, platforms, and scope boundaries.
version: 1.1.0

Arness Discover

Guide a greenfield product idea from raw concept to structured product vision through iterative conversation, aided by product thinking from the `arn-spark-product-strategist` agent, competitive landscape research from `arn-spark-market-researcher`, and persona generation from `arn-spark-persona-architect` (greenfield agents in this plugin). This is a conversational skill that runs in normal conversation (NOT plan mode). The primary artifact is a **product concept document** written to the project's vision directory.

This skill covers the WHAT and WHY of the product, including the **product pillars** -- non-negotiable qualities that define the product's soul and guide all downstream decisions. Technology choices and system design are handled separately by `/arn-spark-arch-vision`.

Step 0: Ensure Configuration (Non-Blocking)

Read `${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-ensure-config/references/step-0-fast-path.md` and follow its instructions. This captures the user profile and configures `## Arness` with Arness Spark fields.

**Important:** This skill is designed for exploratory use before a project may fully exist. If ensure-config encounters errors (e.g., no git repository, CLAUDE.md cannot be created), proceed anyway using fallback defaults: Vision directory = `.arness/vision`, Reports directory = `.arness/reports`. Do not hard-block.

After Step 0 completes (or falls back), determine the output directory: 1. Read the project's `CLAUDE.md` and check for a `## Arness` section 2. If found, extract the configured Vision directory path — this is the source of truth 3. If NOT found (ensure-config fell back), use `.arness/vision` at the project root. 4. If the output directory does not exist, create it

Workflow

Step 1: Capture the Raw Idea

Accept the user's product idea in any form -- a single sentence, a paragraph, or a detailed description. If the idea was included in the trigger message, use it directly. If not, ask:

"What product or tool do you want to build? Describe it in whatever detail you have -- even a rough idea is a good starting point."

After receiving the idea, acknowledge with a brief restatement (2-3 sentences) to confirm understanding. Do not add interpretation or assumptions beyond what the user stated.

Step 2: Initial Analysis with Product Strategist

Invoke the `arn-spark-product-strategist` agent via the Task tool, passing the model from `.arness/agent-models/spark.md` as the `model` parameter (see `plugins/arn-spark/skills/arn-spark-ensure-config/references/ensure-config.md` "Dispatch convention" for fallback). Context:

• The user's raw idea description
• Any context from the conversation so far

The agent returns:

• A vision sketch (initial attempt at a vision statement)
• An assessment of what is clear and what is missing
• 3-5 probing questions organized by priority category
• Scope observations (what looks essential, what could be deferred)

Present the agent's findings to the user as a conversation starter. Frame it as: "Here is my initial read on your idea, with some questions to explore." Do NOT present it as a finished analysis.

Step 3: Guided Discovery Conversation (Iterative)

Enter a conversation loop. The goal is to cover eleven discovery categories, but do so through natural conversation -- not as a sequential questionnaire.

Load the discovery question bank for reference: > Read `${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-discover/references/discovery-questions.md`

Use the product strategist's output from Step 2 to drive the conversation. Start with the categories the agent flagged as weakest. Cover these categories through the conversation (not necessarily in order — the numbering and ordering here differs intentionally from the question bank and template, which are optimized for different purposes):

1. **Vision & Problem** -- what and why 2. **Target Users & Personas** -- who and when (AI-generated personas for validation) 3. **Core Experience** -- the primary interaction 4. **Product Pillars** -- the non-negotiable qualities that define the product's soul 5. **Trust & Security Model** -- how users establish trust 6. **Platform & Constraints** -- where and what limits 7. **Participants & Scale** -- how many, what topology 8. **Scope Boundaries** -- what is NOT v1 9. **Business Model & Constraints** -- revenue model, tenancy, compliance, cost limits 10. **Competitive Landscape** -- alternatives, market positioning (AI-researched) 11. **Assumptions & Success Criteria** -- validated hypotheses, measurable outcomes (AI-derived)

**Product Pillars** deserve special attention. Unlike the other categories which capture facts and decisions, pillars capture convictions. Listen for strong language throughout the conversation -- phrases like "it HAS to feel...", "the whole point is...", "I refuse to compromise on..." are pillar signals. When you hear them, name the pillar back to the user: "It sounds like [quality] is non-negotiable for you -- would you call that a core pillar of this product?" Collect pillars as they emerge naturally rather than asking for them all at once.

AI Assist Checkpoints

**Product type signal:** Early in the conversation (during Step 2 initial analysis or first rounds of Step 3), establish whether this is a **commercial product** (targeting a m