Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add stanislavnianko/product-discovery-claude-skills --skill journey-mappinggit clone --depth 1 https://github.com/stanislavnianko/product-discovery-claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/stanislavnianko/product-discovery-claude-skills/journey-mapping)<a href="https://agentmods.dev/skills/stanislavnianko/product-discovery-claude-skills/journey-mapping"><img src="https://agentmods.dev/badge/skills/stanislavnianko/product-discovery-claude-skills/journey-mapping/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/stanislavnianko/product-discovery-claude-skills/journey-mapping"><img src="https://agentmods.dev/badge/skills/stanislavnianko/product-discovery-claude-skills/journey-mapping.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00080 | $0.01436 |
| Opus 5.5 | $0.00032 | $0.00574 |
| Sonnet 5.5 | $0.00016 | $0.00287 |
| Haiku 4.5 | $0.00008 | $0.00144 |
Grade A, and why
journey-mapping scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Journey Mapping
Part of the discovery-phase skill pack ·
synthesisgroup · readspersonas.md(runpersonasfirst if missing) andthemes.md(frominsight-synthesis).
Turns a persona's lived experience into a stage-by-stage map that surfaces where pain concentrates and where opportunity moments hide. Each pain point is evidence-anchored; each opportunity moment links back to the opportunity-tree.md so journey work doesn't drift from prioritized outcomes.
Step 1 — Read context + upstream artifacts
Read discovery-context.md, personas.md, themes.md. If personas.md is missing, recommend running personas first — journeys without a named persona collapse to "the average user" and become useless. Don't block: the BA may proceed with [ASSUMED-persona] for a quick draft, but flag low confidence.
If interview-notes/ exists, scan for chronological narrative — interviews where users walk through "and then I did…" are gold for journey reconstruction. If only support-data-analysis.md is available, the journey will be partial (post-purchase / support phase only).
Step 2 — Set scope
Decide three things up-front; cram all three into one journey and the map becomes unreadable:
- Which persona — pick exactly one. If you need journeys for two personas, run this skill twice.
- Which journey — onboarding, repeat-purchase, support-resolution, evaluation, churn-recovery, etc. Name it precisely.
- Current-state or future-state — current-state maps pain; future-state maps the proposed redesign. Default to current-state unless a feature-scoping decision depends on the future view.
State all three at the top of the artifact. They're constraints — if mid-skill you find yourself blending personas, stop and re-scope.
Step 3 — Stages (3-7)
High-level phases the persona moves through. Examples by journey type:
| Journey | Typical stages |
|---|---|
| Onboarding | Discover → Sign up → First use → Habit formation |
| Repeat-purchase (B2C) | Trigger → Browse → Decide → Purchase → Receive → Use → Repurchase |
| Support resolution | Hit problem → Self-serve attempt → Contact support → Wait → Resolve |
| Enterprise evaluation | Awareness → Shortlist → Pilot → Internal sell → Procurement → Rollout |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 103 lines · 80 tokens per session scan A e19df9ffdaf8
journey-mapping is a skill published in the GitHub repository stanislavnianko/product-discovery-claude-skills (1 stars, last pushed 5mo ago), licensed MIT. It adds 80 tokens to every session and 1,436 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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