AI Product Development Toolkit is a collection of guided prompts, an AI-built starter for Next.js, Supabase, and Vercel applications, and agent instructions for planning and launching products. It helps people turn an idea into user research, product requirements, user flows, and a web app through an interview-led process. The catalogue entries are its planning and development skills and its Claude Code agent configuration.
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 TechNomadCode/AI-Product-Development-Toolkit --skill user-researchgit clone --depth 1 https://github.com/TechNomadCode/AI-Product-Development-ToolkitWrote 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/technomadcode/ai-product-development-toolkit/user-research)<a href="https://agentmods.dev/skills/technomadcode/ai-product-development-toolkit/user-research"><img src="https://agentmods.dev/badge/skills/technomadcode/ai-product-development-toolkit/user-research/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/technomadcode/ai-product-development-toolkit/user-research"><img src="https://agentmods.dev/badge/skills/technomadcode/ai-product-development-toolkit/user-research.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 | $0.00033 | $0.00226 |
| Opus 5.5 | $0.00013 | $0.00090 |
| Sonnet 5.5 | $0.00007 | $0.00045 |
| Haiku 4.5 | $0.00003 | $0.00023 |
Grade A, and why
user-research 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 3d 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.
What it actually says
This skill has two prompts in its folder. Unless the owner's message makes it clear, ask which one they need:
questionnaire.md: design a questionnaire, before the research.research-to-prd.md: turn collected responses into input for a PRD, after the research.
If a file is missing, tell the owner to install the skills again. Then run the prompt:
- Read it in full and follow it exactly, as if the owner had pasted it.
- Fill its placeholders from the owner: use what's in their message or the files they point to, and ask for the rest. Don't guess.
- When the owner approves the draft, offer to save it as a Markdown file.
What ships with it
1 file 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.
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.
- 3d ago Changed e5f9c4ce871f
- 21d ago First seen · 19 lines · 33 tokens per session scan A fce20f7e3d61
user-research is a skill published in the GitHub repository TechNomadCode/AI-Product-Development-Toolkit (1,023 stars, last pushed 2d ago), licensed MIT. It adds 33 tokens to every session and 226 once invoked, about $0.0001 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 2026-09-25.
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