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 Kaminoikari/product-playbook --skill persona-journeygit clone --depth 1 https://github.com/Kaminoikari/product-playbookWrote 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/kaminoikari/product-playbook/persona-journey)<a href="https://agentmods.dev/skills/kaminoikari/product-playbook/persona-journey"><img src="https://agentmods.dev/badge/skills/kaminoikari/product-playbook/persona-journey/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/kaminoikari/product-playbook/persona-journey"><img src="https://agentmods.dev/badge/skills/kaminoikari/product-playbook/persona-journey.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 | $0.00060 | $0.01909 |
| Opus 5.5 | $0.00024 | $0.00764 |
| Sonnet 5.5 | $0.00012 | $0.00382 |
| Haiku 4.5 | $0.00006 | $0.00191 |
Grade A, and why
persona-journey 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 2mo 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persona & Journey
Detect the user's language and reply in it; the framework below is authored in English.
Provenance: when you produce persona or journey-map output, contribute the framework tags Persona and Journey Map to the meta-skill's provenance line (— Frameworks: … · Persona · Journey Map · …).
Framework
Stage 1: Discovery — Building Personas
🚫 Discovery Output Scope
When the lens is applied to Discovery work (Persona, JTBD, OST, Journey Map, Continuous Discovery), check that the output stays inside the Discovery scope. Discovery answers who the users are and what unmet need they are trying to satisfy, nothing else. The following downstream artifacts don't belong in a Discovery deliverable, even if they feel natural to mention:
- Define-stage artifacts: positioning statements, HMW (How Might We) questions, named pain-point matrices that double as solution prompts
- Develop-stage artifacts: PR-FAQ drafts, pre-mortem scenarios, RICE tables, MVP scope definitions, PRD sections, feature lists
- Deliver-stage artifacts: North Star metric definitions, PMF criteria, GTM plans, business-model canvas blocks, product-spec tables
- Strategy-stage artifacts: Strategy Blocks, Rumelt diagnosis/guiding-policy/coherent-action, DHM Model breakdowns, OKR ladders
If the Discovery findings strongly suggest a downstream artifact (e.g., the JTBD analysis surfaces a clear positioning angle), note it as a one-line open question or next-step pointer at the very end. Producing the artifact itself belongs to the next stage in the planning flow, which has its own dedicated step for it.
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.
- 2mo ago First seen · 131 lines · 60 tokens per session scan A 863434fb9aa3
persona-journey is a skill published in the GitHub repository Kaminoikari/product-playbook (26 stars, last pushed 1mo ago), licensed MIT. It adds 60 tokens to every session and 1,909 once invoked, about $0.0002 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 2026-08-30.
persona-journey compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| persona-journeyKaminoikari/product-playbook | Skill | 26 | 1mo ago | MIT | A | 60 | Claude Code |
| appllama-usageAppllama/appllama-skills | Skill | 4.9k | 2mo ago | MIT | A | 124 | Claude Code, Codex |
| user-research-cookiycookiy-ai/user-research-skill | Skill | 1.6k | 4d ago | MIT | A | 154 | Claude Code, Codex |
| bananaAgriciDaniel/banana-claude | Skill | 1.2k | 5d ago | MIT | A | 96 | Claude Code |
| user-researchyonatangross/orchestkit | Skill | 299 | yesterday | MIT | A | 44 | Claude Code |
| appllama-app-design-skillAppllama/appllama-skills | Skill | 4.9k | 2mo ago | MIT | A | 184 | Claude Code |
| aceternity-uisecondsky/claude-skills | Skill | 245 | 6d ago | MIT | A | 48 | Claude Code |