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 prepforeverything/prepkit-product --skill product-discovery-synthesisgit clone --depth 1 https://github.com/prepforeverything/prepkit-productWrote 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/prepforeverything/prepkit-product/product-discovery-synthesis)<a href="https://agentmods.dev/skills/prepforeverything/prepkit-product/product-discovery-synthesis"><img src="https://agentmods.dev/badge/skills/prepforeverything/prepkit-product/product-discovery-synthesis/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/prepforeverything/prepkit-product/product-discovery-synthesis"><img src="https://agentmods.dev/badge/skills/prepforeverything/prepkit-product/product-discovery-synthesis.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 | $0.00047 | $0.01913 |
| Opus 5 | $0.00023 | $0.00957 |
| Sonnet 5 | $0.00009 | $0.00383 |
| Haiku 4.5 | $0.00005 | $0.00191 |
Grade A, and why
product-discovery-synthesis 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 10d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Standalone Mode: This skill is part of the prepkit-product plugin.
spec/product-context.mdis optional — provide context inline or create one from the template.- Output paths (
research/,reports/) are relative to your current working directory.- Facilitation routing is advisory — invoke any skill directly.
Product Discovery Synthesis
When To Use
- An incoming feature request needs reframing into a user problem
- The team is debating solutions before the job and pain are clear
spec/product-context.mdhas weak or assumed discovery inputs- Discovery evidence exists but has not been shaped into an opportunity worth mapping
- Discovery has interview evidence but opportunities feel fragmented across multiple touchpoints or phases
Key Concepts
- Jobs-to-be-Done (JTBD): users hire products to make progress in a context
- Opportunity space: unmet needs or frictions that exist before solution ranking
- Switching forces: push, pull, anxiety, and habit explain why users change
- Outcome framing: opportunities should connect to user progress and measurable change
- Empathy mapping: collaborative synthesis artifact that organises interview observations into four quadrants — Says (verbatim quotes), Thinks (internal beliefs not spoken aloud), Does (observable behaviours), and Feels (emotional states). Use it after interviews and before JTBD synthesis to ensure the Thinks and Feels dimensions — which affinity mapping alone does not prompt for — are explicitly captured. Juxtapositions across quadrants (e.g. positive Does but negative Feels) often reveal the most actionable unmet needs. See
references/empathy-mapping-synthesis.md. - Customer journey mapping: visualisation of the user experience across phases — capturing what users do, think, and feel at each stage — to surface friction points and opportunity areas across the full experience arc. ODI Job Map (eight functional steps) is the right tool for deep single-job analysis; journey mapping covers multi-touchpoint experiences, emotional peaks, and cross-channel friction that JTBD interviews alone may not surface. The opportunities layer of a journey map is a direct input to OST opportunity nodes. See
references/journey-mapping-basics.md. - Design Thinking / HCD process framing: teams with design-background practitioners often use the Empathize-Define-Ideate-Prototype-Test model (Design Thinking) or the ISO 9241-210 four-activity HCD cycle as their process reference. These are complementary framings alongside JTBD/ODI, not replacements. Empathize maps to JTBD interviewing; Define maps to empathy and journey mapping synthesis; Ideate maps to OST solution generation; Prototype/Test map to assumption-driven experimentation. JTBD and ODI remain the primary analytical frameworks in this skill; Design Thinking provides cross-disciplinary orientation for mixed teams.
- First-principles decomposition: when discovery is stuck, a framework produces conflicting signals, or the problem framing feels inherited rather than earned, decompose the core assumption to axiomatic truths before continuing. First-principles is a meta-tool that works alongside JTBD, HCD, RICE, and other frameworks — it clears the foundation so those frameworks produce better answers. See
references/first-principles-thinking.md.
What ships with it
8 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.
- references/empathy-mapping-synthesis.md 5.5 KB
- references/first-principles-thinking.md 6.1 KB
- references/journey-mapping-basics.md 6.3 KB
- references/jtbd-framework.md 2.0 KB
- references/opportunity-solution-tree.md 2.0 KB
- references/outcome-driven-innovation.md 3.1 KB
- references/product-quality-gates.md 1.5 KB
- references/user-research-patterns.md 2.5 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.
- 10d ago First seen · 106 lines · 47 tokens per session scan A c3536b4d43f5
product-discovery-synthesis is a skill published in the GitHub repository prepforeverything/prepkit-product (2 stars, last pushed 5mo ago), licensed MIT. It adds 47 tokens to every session and 1,913 once invoked, about $0.0002 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 2026-08-31.
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