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 ljucask/pureinn-product-development --skill pm-hypothesesgit clone --depth 1 https://github.com/ljucask/pureinn-product-developmentWrote 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/ljucask/pureinn-product-development/pm-hypotheses)<a href="https://agentmods.dev/skills/ljucask/pureinn-product-development/pm-hypotheses"><img src="https://agentmods.dev/badge/skills/ljucask/pureinn-product-development/pm-hypotheses/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/ljucask/pureinn-product-development/pm-hypotheses"><img src="https://agentmods.dev/badge/skills/ljucask/pureinn-product-development/pm-hypotheses.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 | $0.00000 | $0.05106 |
| Opus 5 | $0.00000 | $0.02553 |
| Sonnet 5 | $0.00000 | $0.01021 |
| Haiku 4.5 | $0.00000 | $0.00511 |
Grade A, and why
pm-hypotheses 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 — 461 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM - Hypothesis Validation
Agent mode (--agent)
This skill's value is the live dialogue - --agent is not supported. If invoked with --agent, warn once ("this skill needs interactive back-and-forth; agent mode would hollow it out") and proceed interactively.
What this skill does
Turns raw assumptions into structured, testable hypotheses. Assigns the right experiment to each hypothesis. Tracks evidence as experiments run. Produces a Go/No-Go decision with pre-defined success metrics.
This skill runs in two modes:
- Plan mode (first run): structure hypotheses from design-thinking outputs, rank by risk, assign experiment types, define success criteria before any experiment runs
- Results mode (follow-up run): record experiment outcomes, update hypothesis status, issue Go / Pivot / Stop decision
Both modes use the same artifact - the Hypothesis Register - which is updated progressively.
Why validate this way
Most startups fail not because of bad ideas but because they build solutions for problems that are not painful enough. Skipping structured validation means:
- Months of engineering for a product nobody buys
- No ability to distinguish signal from noise in early feedback
- Confirmation bias: founders hear what they want to hear
The goal of validation is not to get a yes or no. It is to learn. Every experiment is a clue that reduces uncertainty before capital and engineering time are committed.
Validation stages
This skill covers the full 5-stage validation arc:
| Stage | Goal | Primary method |
|---|---|---|
| 1 - Hypothesis | Define riskiest assumptions about problem, customer, solution, market | Assumption map + hypothesis register |
| 2 - Qualitative | Understand pain points and context from real people | Customer discovery interviews (The Mom Test approach) |
| 3 - Quantitative | Measure real-world demand with low-cost experiments | Landing page, smoke test, pre-order, targeted ads |
| 4 - Lightweight MVP | Test value delivery with minimum build | Concierge MVP, Wizard of Oz, no-code prototype |
| 5 - Go/No-Go | Evidence-based decision: go, pivot, or stop | Success metric review, decision table |
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 · 461 lines · 0 tokens per session scan A 7a54b370fc2b
pm-hypotheses is a skill published in the GitHub repository ljucask/pureinn-product-development (2 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 5,106 tokens. 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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