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 | $0.00033 | $0.01684 |
| Sonnet 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 12d 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.
- 12d ago First seen · 182 lines · 66 tokens per session scan A b263bc6bfe42
jtbd is a skill published in the GitHub repository Kaminoikari/product-playbook (24 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. 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.
Other skills, from other repositories
hps-true-blueprint
OpenDesign's engineering blueprint: how the sandbox, sidecar, and daemon fit — the system diagram and the invariants. Built as a decision-grade product management deck for engineering org.
deck-open-slide-canvas
OpenDesign's architecture review: the local daemon + agent-runtime design, the tradeoffs, and the decision to lock. Built as a decision-grade product management deck for staff eng, tech leads, security.
banana
Direct, generate, edit, compare, and review visual assets with current Google Gemini image models. Use for image creation, image editing, reference-based consistency, product and character visuals, text-bearing graphics, grounded diagrams, video-derived images, and multi-model image portfolios.
tool-design-sprint-prototype-plan
Day 4 (Thursday) move of a Design Sprint that produces the planning artifact for the day. Output covers the prototype role plan (Maker, Stitcher, Writer, Asset Collector, Interviewer), prototype brief (what to build, fidelity bar, time allocation per role), canonical Five-Act Interview script (Welcome, Context, Intro…
tool-design-sprint-readiness
Pre-sprint diagnostic that determines whether a team should run a Design Sprint now, postpone it, or do prerequisite work first. Produces a Go / Conditional Go / Wait verdict with diagnosis, recommended preconditions, attendee list, customer recruiting plan, and pre-sprint activities. Use when a team is considering…
aceternity-ui
100+ animated React components (Aceternity UI) for Next.js with Tailwind. Use for hero sections, parallax, 3D effects, or encountering animation, shadcn CLI integration errors.