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 calionauta/stelow --skill stelow-product-discoverygit clone --depth 1 https://github.com/calionauta/stelowWrote 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/calionauta/stelow/stelow-product-discovery)<a href="https://agentmods.dev/skills/calionauta/stelow/stelow-product-discovery"><img src="https://agentmods.dev/badge/skills/calionauta/stelow/stelow-product-discovery/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/calionauta/stelow/stelow-product-discovery"><img src="https://agentmods.dev/badge/skills/calionauta/stelow/stelow-product-discovery.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 | $0.00137 | $0.01946 |
| Opus 5 | $0.00068 | $0.00973 |
| Sonnet 5 | $0.00027 | $0.00389 |
| Haiku 4.5 | $0.00014 | $0.00195 |
Grade A, and why
stelow-product-discovery 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.
How it starts
The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product with Short Learning Cycles
This guide is a method to replace speculation with evidence, step by step. Core principle: experiment before building. Reduce uncertainty with small, fast, and cheap experiments.
"Life is too short to build something that nobody wants." — Ash Maurya
Method Structure
The process has 8 stages (not necessarily linear):
- Find and understand the audience
- Define the market
- Define and prioritize solutions
- Develop and evaluate the offer
- Assess commitment
- Discover the process
- Evolve to a viable business
- The pulse of the system: signals in tension
→ Read reference files as needed:
references/01-experimentation-principles.md— criteria for reliable data + 6 principlesreferences/02-stages-1-to-3.md— audience, market, solutionsreferences/03-stages-4-to-6.md— offer, commitment, manual processreferences/04-stage-7.md— viable business, product-market fit, channelsreferences/05-stage-8-signals.md— pulse of the system, signals in tensionreferences/06-appendix-business-models.md— business models, open source, pricingreferences/07-appendix-strategies.md— marketplace, solutions, trust, bonuses, promotions, ads, lifecycle
When to Read Each Reference
| User asks about... | Read... |
|---|---|
| How to validate an idea / experiment | 01, 02 |
| Target audience, market, jobs to be done | 02 |
| Solution, product, features | 02, 03 |
| Offer, advertisement, early adopters | 03 |
| Pre-sale, commitment, waitlist | 03 |
| MVP, manual process, concierge, wizard of oz | 03 |
| Product-market fit, channels, viable business | 04 |
| Metrics, retention, growth | 04, 05 |
| Pricing, pricing models | 06 |
| Business models, revenue, costs | 06 |
| Open source as strategy | 06 |
| Marketplace, supply and demand | 07 |
| Trust, guarantees, social proof | 07 |
| Bonuses, launch promotions | 07 |
| Online ads, stages of awareness | 07 |
| Product lifecycle, innovation | 07 |
Interaction Tool Guidelines
What ships with it
7 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.
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 · +22 lines d5f204f9fa60
- 12d ago First seen · 171 lines · 137 tokens per session scan A 9a0252686db0
stelow-product-discovery is a skill published in the GitHub repository calionauta/stelow (10 stars, last pushed today), licensed MIT. It adds 137 tokens to every session and 1,946 once invoked, about $0.0007 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.
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