Journey Mapper

Reads a codebase, thinks like a service designer, and writes a single browser-ready HTML file with all inferred user journeys and service blueprints.

See REFERENCE.md in this skill's base directory for the JSON schema, NN/g methodology notes, and emotional arc heuristics.

Quick start

If the codebase is not already in scope, ask:

"Which directory should I scan? And where should I save the output HTML?"

Workflow

1. Gather context — ask for anything not already in scope:

Input	Default
Codebase path	Required — ask if missing
Output path	journey-map.html in codebase root
Product name	Used in the HTML title and rail heading
Extra context	Design docs, research, README, API specs
Scope	Full scan, or specific subdirectory for large codebases

2. Scan the codebase — dispatch Explore, or use Grep + Read for targeted sweeps. Extract:

• Routes, screens, page components, entry points
• Auth roles, user types, permission models, tenant structures
• Onboarding flows, auth gates, redirect chains, feature flags
• API endpoints, background jobs, third-party integrations
• Email templates, push notifications, in-app alerts, webhook payloads
• Error states, empty states, loading patterns, blocked or warning states

For large codebases: routes first → components → API layer → notifications.

3. Organise into NN/g structure — think as a service designer:

• 2–5 actors — who uses the system (infer from auth roles, user types, API consumers)
• 3–6 categories — thematic groups (Onboarding, Core workflow, Admin, Recovery, Alternative paths…)
• 4–12 journeys — one per meaningful end-to-end scenario; cover golden paths first, then error/recovery
• Each journey → 2–5 stages → 2–4 moments per stage

Per-moment fields to fill — every inferred value gets [Assumption] prefix:

Field	Notes
doing	What the user physically does. Factual. No [Assumption].
frontstage	What they see: UI, email, native prompt. Factual.
backstage	What the code does behind the scenes. Factual.
support	Which system, service, or API underpins this. Factual.
thinking	[Assumption] — inferred user thought at this moment.
feeling	Integer 1–5 (1 = very frustrated, 5 = delighted). Use 2–3 for friction-heavy moments.
pain	[Assumption] — inferred friction point.
opportunity	[Assumption] — inferred improvement idea.
evidence	Leave blank "" — the human fills this from user research.

See REFERENCE.md for emotional arc heuristics and a worked example.

4. Generate the HTML:

1. Read TEMPLATE.html from this skill's base directory (shown above when skill loads).
2. Replace <title>Journey Maps</title> with <title>[Product name] — Journey Maps</title>.
3. Replace the .rail h1 text Journey Maps with the product name.
4. Replace only the <script type="application/json" id="journeys-data">…</script> block with your generated JSON.
5. Write the complete file to the output path. Do not modify anything else in the template.

5. Report back:

• Path the file was saved to
• Journey count · moment count · category count
• Coverage gaps: flows or actor types with thin codebase evidence
• 2–3 standout pain points inferred from error states, friction-heavy flows, or complex conditionals