Question-first approach to understanding user journeys. Load when starting a new journey design or when the discovery phase needs deepening.
npx skills add https://github.com/nWave-ai/nWave --skill nw-discovery-methodology
Discover journeys through deep questioning before any sketching. The sketch is proof of understanding, not the starting point.
Focus: What is the user trying to accomplish?
Questions:
After collecting goal, trigger, and success criteria, output a rough draft sketch showing what the journey might look like. Mark unknowns with ???. Purpose: make value visible immediately so the user sees progress, not just questions.
[Trigger: ???] → [Step 1: ???] → [Step 2: ???] → [Goal: {stated goal}]
Feels: ??? Sees: ??? Sees: ??? Feels: {success criteria}
Artifacts: ??? Artifacts: ??? Artifacts: ???
This is a working hypothesis, not a commitment. Update it after each phase as understanding deepens. The sketch gives the user something concrete to react to — "no, step 2 happens before step 1" is more productive than abstract discussion.
Focus: What does the user EXPECT to see?
Questions:
Focus: How should the user FEEL?
Questions:
Focus: What data is shared across steps?
Questions:
Focus: What could go wrong?
Questions:
Focus: How do steps connect?
Questions:
Focus: What commands and output does the user expect?
Questions:
Use AskUserQuestion with structured options:
Ready to sketch ONLY when all can be answered:
If ANY criterion is unclear -- ask more questions.
Always ask first when:
Continue asking until:
Instead:
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Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take nwave-ai/nw-discovery-methodology from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.