nw-discover
nw-discover conducts structured product discovery by validating core business assumptions through customer interviews and market testing, using Mom Test principles to establish problem-solution fit. Teams should deploy this skill at project inception to test whether a proposed solution addresses a real customer problem before committing to design and development work.
git clone --depth 1 https://github.com/nWave-ai/nWave /tmp/nw-discover && cp -r /tmp/nw-discover/nWave/skills/nw-discover ~/.claude/skills/nw-discoverSKILL.md
# NW-DISCOVER: Evidence-Based Product Discovery
**Wave**: DISCOVER | **Agent**: Scout (nw-product-discoverer)
## Overview
Execute evidence-based product discovery through assumption testing and market validation. First wave in nWave (DISCOVER > DISCUSS > SPIKE > DESIGN > DEVOPS > DISTILL > DELIVER).
Scout establishes product-market fit through rigorous customer development using Mom Test interviewing principles and continuous discovery practices.
## Output Tiers (per D2)
Provenance: feature `lean-wave-documentation` — D2 (schema-typed sections), D10 (one-line expansion descriptions). Tier-1 [REF] sections (always emitted) + Tier-2 EXPANSION CATALOG items (lazy, on-demand) are the two output bands. Full contract + provenance for `[REF]` / `[WHY]` / `[HOW]` heading convention: `nWave/skills/nw-density-resolution-contract/SKILL.md`.
### Tier-1 [REF] — always emitted
Under `## Wave: DISCOVER / [REF] <Section>` headings:
- Persona ID — one-line user identifier mapped to the journey
- Opportunity statement — single-sentence problem/opportunity framing
- Validated assumptions — list with confidence level per item
- Invalidated assumptions — list with evidence reference per item
- Dropped options — alternatives weighed and rejected (one-line each)
- Decision gate (G1-G4) — pass/fail status per gate
- Constraints established — evidence-backed constraints from interviews
- Pre-requisites — dependencies on prior waves or features
### Tier-2 EXPANSION CATALOG — lazy, on-demand (per D10)
Rendered under `## Wave: DISCOVER / [WHY|HOW] <Section>` only when requested via `--expand <id>` (DDD-2), the wave-end menu (`expansion_prompt = "ask"`), `mode = "full"` auto-expansion, or an ad-hoc user request mid-session.
| Expansion ID | Tier label | One-line description |
|---|---|---|
| `discovery-interview-transcripts` | [WHY] | Full interview transcripts with verbatim quotes (Mom Test compliance evidence) |
| `jtbd-analysis` | [WHY] | Jobs-to-be-Done analysis: functional/emotional/social dimensions per job |
| `taste-evaluation-rationale` | [WHY] | Decision rationale for each evaluated opportunity (why fit, why not) |
| `alternative-opportunities` | [WHY] | Alternative product opportunities considered and rejected |
| `four-forces-narrative` | [WHY] | Push/Pull/Anxiety/Habit narrative analysis per primary job |
| `lean-canvas-walkthrough` | [HOW] | Lean canvas section-by-section walkthrough for stakeholder reviews |
| `interview-protocol` | [HOW] | Step-by-step interview script with Mom Test follow-up patterns |
| `expansion-catalog-rationale` | [WHY] | Why this set of expansions, why these defaults, why D10 enforces one-line descriptions |
## Density resolution (per D12)
Call `resolve_density(global_config)` from `scripts/shared/density_config.py` after reading `~/.nwave/global-config.json` (missing/malformed = empty dict). Returns `mode` (`"lean"` | `"full"`) + `expansion_prompt` (`"ask"` | `"always-skip"` | `"always-expand"` | `"smart"`) per the D12 cascade (resolver-internal, DDD-5 — do NOT replicate locally). Branch on `density.mode` for what to emit; branch on `density.expansion_prompt` at wave end for menu behaviour. Full cascade detail, branch semantics, ad-hoc override workflow ("expand X" / "tell me why"): `nWave/skills/nw-density-resolution-contract/SKILL.md`.
## Telemetry (per D4 + DDD-6)
Every expansion choice emits a `DocumentationDensityEvent` (dataclass at `src/des/domain/telemetry/documentation_density_event.py`) via `event.to_audit_event()` → `JsonlAuditLogWriter().log_event(...)`. Schema fields per D4: `feature_id`, `wave`, `expansion_id`, `choice`, `timestamp`. For this wave the schema declares `"wave": "DISCOVER"`. Use helper `scripts/shared/telemetry.py:write_density_event(...)` — do NOT write JSONL directly.
Wave-specific signal: DISCOVER feeding into DISCUSS — downstream `--expand` invocations are a signal the lean baseline is too thin. Full emission rules (one event per `ask` choice; synthetic skip event for `always-skip`; per-item expand event for `full` / `always-expand`): `nWave/skills/nw-density-resolution-contract/SKILL.md`.
## Context Files Required
- docs/project-brief.md — Initial product vision (if available)
- docs/market-context.md — Market research and competitive landscape (if available)
## Previous Artifacts
None (DISCOVER is the first wave).
## Wave Decisions Summary
Before completing DISCOVER, produce `docs/feature/{feature-id}/discover/wave-decisions.md`:
1. **Record Key Decisions** — List each decision as `[D1] {decision}: {rationale} (see: {source-file})`. Gate: every major discovery choice has a rationale entry.
2. **Record Constraints** — List each constraint established from evidence. Gate: all constraints have an evidence source.
3. **Record Validated Assumptions** — List each assumption confirmed, with confidence level. Gate: confidence level stated for each.
4. **Record Invalidated Assumptions** — List each assumption disproved, with evidence reference. Gate: evidence reference present for each invalidation.
This summary enables downstream waves to quickly assess DISCOVER outcomes without reading all artifacts.
## Document Update (Back-Propagation)
DISCOVER is the first wave but it DOES write to SSOT. It has no prior wave to back-propagate to, but it seeds the SSOT for downstream waves:
1. **Seed journeys** — Write initial `docs/product/journeys/{name}.yaml` with the persona, opportunity statement, and the discovered job(s) traced from interviews. DISCUSS will refine and lock this schema.
2. **Seed personas (optional)** — When persona-narrative expansion is triggered, write `docs/product/personas/{name}.yaml` with the validated persona profile. Otherwise leave to DISCUSS.
3. **No prior-wave Changed-Assumptions section** — DISCOVER produces evidence; it does not contradict prior decisions because there are none. The Changed-Assumptions pattern starts in DISCUSS.
Per D5 (lean-wave-documentation): DISCOVER's `docs/product/journeys/`Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
Review dimensions for acceptance test quality - happy path bias, GWT compliance, business language purity, coverage completeness, walking skeleton user-centricity, priority validation, observable behavior assertions, traceability coverage, and walking skeleton boundary proof
Detailed 5-phase workflow for creating agents - from requirements analysis through validation and iterative refinement
5-layer testing approach for agent validation including adversarial testing, security validation, and prompt injection resistance
Architectural style selection decision matrices, trade-off analysis, structural enforcement rules, and combination patterns. Load when choosing or evaluating architecture styles.
Comprehensive architecture patterns, methodologies, quality frameworks, and evaluation methods for solution architects. Load when designing system architecture or selecting patterns.
Canonical AT completeness gate — research-anchored 7-category taxonomy (C1-C7) + 15-item mechanical checklist. Paradigm-neutral. Drives acceptance-designer reviewer verdict deterministically.