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 wdavidturner/product-skills --skill jobs-to-be-donegit clone --depth 1 https://github.com/wdavidturner/product-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/wdavidturner/product-skills/jobs-to-be-done)<a href="https://agentmods.dev/skills/wdavidturner/product-skills/jobs-to-be-done"><img src="https://agentmods.dev/badge/skills/wdavidturner/product-skills/jobs-to-be-done/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/wdavidturner/product-skills/jobs-to-be-done"><img src="https://agentmods.dev/badge/skills/wdavidturner/product-skills/jobs-to-be-done.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 | $0.00078 | $0.00961 |
| Opus 5 | $0.00039 | $0.00481 |
| Sonnet 5 | $0.00016 | $0.00192 |
| Haiku 4.5 | $0.00008 | $0.00096 |
Grade A, and why
jobs-to-be-done 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jobs-to-be-Done (JTBD)
What It Is
Jobs-to-be-Done is a framework for understanding customer motivation. The core insight: people don't buy products, they hire them to make progress in their lives.
When someone buys a product, they're not buying features or benefits—they're hiring that product to do a job. Understanding that job unlocks everything: positioning, messaging, feature prioritization, and competitive strategy.
The key shift: Move from asking "What do customers want?" to asking "What progress are customers trying to make?"
When to Use It
Use JTBD when you need to:
- Understand why customers buy (not just what they buy)
- Discover your true competitive set (often not who you think)
- Find product-market fit for a new product or feature
- Improve positioning and messaging that resonates
- Reduce churn by understanding why customers leave
- Prioritize your roadmap based on real customer progress
- Identify new market opportunities through struggling moments
When Not to Use It
- There's no real customer choice (e.g., employer-mandated software)
- The purchase is pure habit with no conscious decision
- You want to validate a hypothesis you've already decided on
Patterns
Detailed examples showing how to apply JTBD correctly. Each pattern shows a common mistake and the correct approach.
Critical (get these wrong and you've wasted your time)
| Pattern | What It Teaches |
|---|---|
| interview-asking-why | Don't ask "why did you buy" — ask "walk me through what happened" |
| job-statement-too-broad | "Save time" is useless — needs context + motivation + outcome |
| missing-forces | Analyze all four forces, not just Push and Pull |
| interviewing-prospects | Only interview people who already switched |
| conference-room-jtbd | You can't hypothesize jobs without talking to customers |
What ships with it
16 files 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.
- patterns/_template.md 460 B
- patterns/clustering-vs-segmenting.md 1.9 KB
- patterns/complaints-arent-jobs.md 1.5 KB
- patterns/conference-room-jtbd.md 1.7 KB
- patterns/context-changes-everything.md 1.8 KB
- patterns/following-power-users.md 1.6 KB
- patterns/getting-past-pablum.md 2.0 KB
- patterns/interview-asking-why.md 1.2 KB
- patterns/interviewing-prospects.md 1.5 KB
- patterns/job-statement-too-broad.md 1.4 KB
- patterns/milkshake-story.md 2.7 KB
- patterns/missing-forces.md 1.6 KB
- patterns/reducing-friction.md 1.6 KB
- patterns/three-energies.md 1.5 KB
- patterns/wrong-competitors.md 1.4 KB
- references/jobs-to-be-done-playbook.md 12 KB
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 · 84 lines · 78 tokens per session scan A bc776c42f53a
jobs-to-be-done is a skill published in the GitHub repository wdavidturner/product-skills (20 stars, last pushed 7mo ago), licensed MIT. It adds 78 tokens to every session and 961 once invoked, about $0.0004 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…