/arn-spark-stress-interview

name: arn-spark-stress-interview
description: >-
  This skill should be used when the user says "stress interview",
  "synthetic interview", "user interview stress test", "interview my personas",
  "test with synthetic users", "persona interview", "simulate user interviews",
  "run user interviews", or wants to stress-test a product concept by conducting
  structured interviews with synthetic personas through three adversarial lenses
  (Pragmatist, Skeptic, Power User). Produces an interview report with
  per-persona findings, synthesized themes, and recommended concept updates.
version: 1.0.0

Arness Spark Stress Interview

Stress-test a product concept by conducting structured synthetic user interviews. This skill generates 3 synthetic personas from the product concept's persona moulds, applies adversarial casting overlays (Pragmatist, Skeptic, Power User), and runs each through a 3-phase "Two-Part Reveal" interview protocol:

1. **Phase 1 -- Blind Problem Check:** The persona hears about the problem without knowing the product exists. Do they even care? 2. **Phase 2 -- Elevator Pitch Reveal:** The full product concept is revealed. What resonates? What falls flat? What is missing? 3. **Phase 3 -- Dealbreaker Probe:** The weakest aspects are presented head-on. Would they still use this?

The process produces brutally honest feedback from 3 distinct adversarial perspectives, synthesized into actionable concept update recommendations. The product concept is read but never modified -- all recommendations are captured in the interview report for later review.

Prerequisites

Configuration Check

1. Read the project's `CLAUDE.md` and check for a `## Arness` section 2. If found, extract the configured **Vision directory** and **Reports directory** paths 3. If no `## Arness` section exists or Arness Spark fields are missing, inform the user: "Arness Spark is not configured for this project yet. Run `/arn-brainstorming` to get started — it will set everything up automatically." Do not proceed without it. 4. Create the reports directory structure if it does not exist: `mkdir -p <reports-dir>/stress-tests/`

Data Availability

| Artifact | Status | Location | Fallback | |----------|--------|----------|----------| | Product concept | REQUIRED | `<vision-dir>/product-concept.md` | Cannot proceed without it -- suggest running `/arn-spark-discover` | | Persona moulds | REQUIRED | Target Personas section of product concept | Fallback cascade below | | Product pillars | ENRICHES | Product Pillars section of product concept | Interview proceeds but questions are less targeted | | Competitive landscape | ENRICHES | Competitive Landscape section of product concept | Phase 3 competitive comparison questions are skipped |

**Persona moulds fallback cascade:**

If the product concept exists but the Target Personas section is missing or contains "Not explored" sentinel:

Ask (using `AskUserQuestion`): **"The product concept does not include persona moulds, which are needed to generate synthetic interview subjects. How would you like to proceed?"** 1. Run `/arn-spark-discover` to generate personas through product discovery 2. Describe 3 target user types now (I will generate personas from your descriptions) 3. Skip the interview stress test

If the user chooses option 2, collect brief descriptions and invoke `arn-spark-persona-architect` in **instantiation mode** to generate persona instances with casting overlays before proceeding.

Workflow

Step 1: Load References

Load the interview protocol, persona casting spec, and report template: > Read `${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-stress-interview/references/interview-protocol.md` > Read `${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-stress-interview/references/persona-casting-spec.md` > Read `${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-stress-interview/references/interview-report-template.md`

Step 2: Read Product Concept and Extract Context

Read the product concept from `<vision-dir>/product-concept.md`. Extract:

• Product vision and problem statement (for Phase 1 blind problem check)
• Full product concept summary (for Phase 2 reveal)
• Product pillars (for targeted probing)
• Competitive landscape (for Phase 3 competitive comparisons)
• Persona moulds from the Target Personas section
• Scope boundaries and deferred features (for Phase 3 dealbreaker probes)

Step 3: Generate Synthetic Personas (Casting)

Select 3 persona moulds from the product concept. If more than 3 moulds exist, select the 3 most diverse in adoption posture and technical sophistication.

For each mould, invoke the `arn-spark-persona-architect` agent in **instantiation mode** 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:

--- PERSONA MOULD --- [full abstracted profile from product concept] --- END PERSONA MOULD ---

--- CASTING OVERLAY --- [overlay specification from persona-casting-spec.md -- one of Pragmatist, Skeptic, Power User] --- END CASTING OVERLAY ---

--- PRODUCT CONTEXT --- [product vision and problem statement for domain grounding] --- END PRODUCT CONTEXT ---

Assign overlays following the priority in the casting spec: natural fit first, then maximize coverage.

Receive back 3 fully detailed concrete personas with casting overlays baked in. Present a brief summary to the user:

"I have generated 3 synthetic interview subjects:

• **[Persona 1 Name]** ([Archetype]) with **Pragmatist** lens -- focused on practical adoption barriers
• **[Persona 2 Name]** ([Archetype]) with **Skeptic** lens -- focused on trust and systemic risk
• **[Persona 3 Name]** ([Archetype]) with **Power User** lens -- focused on depth and scalability

Starting interviews now. Each persona goes through 3 phases: blind problem check, full reveal, and dealbreaker probe."

Step 4: Conduct Interviews