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 jtbdgit 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/jtbd)<a href="https://agentmods.dev/skills/kaminoikari/product-playbook/jtbd"><img src="https://agentmods.dev/badge/skills/kaminoikari/product-playbook/jtbd/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/jtbd"><img src="https://agentmods.dev/badge/skills/kaminoikari/product-playbook/jtbd.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00066 | $0.03369 |
| Opus 5.5 | $0.00026 | $0.01348 |
| Sonnet 5.5 | $0.00013 | $0.00674 |
| Haiku 4.5 | $0.00007 | $0.00337 |
Grade A, and why
jtbd 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jobs To Be Done
Detect the user's language and reply in it; the framework below is authored in English.
Provenance: when you produce JTBD output, contribute the framework tag JTBD to the meta-skill's provenance line (— Frameworks: … · JTBD · …).
Framework
Phase 1: Discovery — JTBD Analysis
1.3 JTBD (Jobs to Be Done) Analysis
"The unit of analysis is not the consumer, but the job the consumer is trying to get done." — Clayton Christensen
JTBD Three-Layer Coverage (quality check: cover all three layers):
A complete JTBD analysis covers all three layers explicitly: Functional (the task being completed), Emotional (how the user wants to feel during/after), and Social (how the user wants to be perceived). Producing only the Functional layer is the most common JTBD failure: Emotional and Social Jobs are routinely the real switching triggers, especially in B2B. If a single Persona genuinely has no meaningful Emotional or Social Job for the product, state that explicitly with one sentence of reasoning; do not silently omit the row.
JTBD Canonical Form (quality check: three-clause structure):
Every JTBD statement in every layer (Primary, Functional, Emotional, Social) is written as a complete three-clause sentence in the canonical form. All three clauses matter:
When [situation], I want to [motivation], so [outcome].
Failing examples (fragments inside a table cell, missing clauses):
- ❌ "Quickly capture key takeaways" (missing When; missing so)
- ❌ "Jot down ideas during commute" (missing I want to; missing so outcome)
Passing example (all three clauses present):
- ✅ "When I've just finished reading an article and the key insight is still fresh, I want to capture one takeaway in 5 seconds, so weeks later I can still find it and connect it to a new idea."
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 · 182 lines · 66 tokens per session scan A b263bc6bfe42
jtbd is a skill published in the GitHub repository Kaminoikari/product-playbook (26 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 3,369 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 2026-08-30.
jtbd compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| jtbdKaminoikari/product-playbook | Skill | 26 | 1mo ago | MIT | A | 66 | 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 |