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NW-DISCOVER: Evidence-Based Product Discovery · nwave-ai | DecimalAI

researchby nwave-ai

NW-DISCOVER: Evidence-Based Product Discovery

nwave-ai/nw-discover

Source nwave-ai/nwave ↗License MIT

Conducts evidence-based product discovery through customer interviews and assumption testing. Use at project start to validate problem-solution fit.

SkillScore83Maintained

Automatic

Product Management pack

Last verified 8/28/2026

What it changes

Passed 17 of 21 test cases with the skill, and 3 of 21 without it.

Without skill13%

With skill83%

Checks it passed that the model alone missed

Formats each dropped option as a single-line summary.
Uses the expansion identifier lean-canvas-walkthrough.
Emits a skip event when evaluating density menu triggers.

and 23 more in the full report

17 fixed3 passed either way4 still failing0 broke

Pass-rate lift: +71 pp
Tokens: +60%
Agent turns: 0%
Response time: -46%

Model gemini-3.6-flashMeasured 8/28/2026v220 of 24 cases passed with skill · 21 comparable

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/nwave-ai-nw-discover/SKILL.md https://app.decimal.ai/s/nwave-ai-nw-discover/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add nwave-ai-nw-discover, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/nwave-ai-nw-discover/ and pins it in .decimal/skills.lock

decimalai skills add nwave-ai-nw-discover

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/nwave-ai-nw-discover/SKILL.md https://app.decimal.ai/s/nwave-ai-nw-discover/SKILL.md

Raw file: /s/nwave-ai-nw-discover/SKILL.md ↗ · machine-readable summary at /s/nwave-ai-nw-discover.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 17 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 17

Prompt

After completing initial market discovery for asset-tracker, we want to perform peer review before handoff to the product owner in DISCUSS. The team is considering running up to 5 iterative review attempts if revisions are needed. Which reviewer agent handles this gate, and what is the maximum allowed revision attempt count before mandatory escalation?

What was checked, without and with the skill
Checked	Without skill	With skill
Invokes @nw-product-discoverer-reviewer to perform the peer review gate.	Missed	Passed
Enforces a maximum threshold of 2 review attempts before escalating to the user.	Missed	Passed

case-08 · gemini-3.6-flash · 8/28/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md129 linessingle file

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 broad wave-end menu (expansion_prompt = "ask"), a declared trigger under expansion_prompt = "ask-intelligent", 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

Track record

Benchmark

17 / 21

test cases passed, vs 3 / 21 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v5 — 8/26/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

nwave-ai / nwave

nWave/skills/nw-discover/SKILL.md

View on GitHub ↗

License MITImported 8/26/2026Version v2

Other skills for the same job

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nwave-ai/nw-discussConducts Jobs-to-be-Done analysis, UX journey design, and requirements gathering through interactive discovery. Use when starting feature analysis, defining user stories, or creating acceptance criteria.Close match+50 pp pass-rate lift

More skills from the same source and nearby in the registry, with their headline benchmark lift.

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See it in action

What's inside

NW-DISCOVER: Evidence-Based Product Discovery

Overview

Output Tiers (per D2)

Tier-1 [REF] — always emitted

Tier-2 EXPANSION CATALOG — lazy, on-demand (per D10)

Track record

Benchmark

Adoption

SkillSafety

Source

Other skills for the same job

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