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 Uxcel-Lab/product-skills --skill vision-strategygit clone --depth 1 https://github.com/Uxcel-Lab/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/uxcel-lab/product-skills/vision-strategy)<a href="https://agentmods.dev/skills/uxcel-lab/product-skills/vision-strategy"><img src="https://agentmods.dev/badge/skills/uxcel-lab/product-skills/vision-strategy/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/uxcel-lab/product-skills/vision-strategy"><img src="https://agentmods.dev/badge/skills/uxcel-lab/product-skills/vision-strategy.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 | $0.00177 | $0.03956 |
| Opus 5 | $0.00088 | $0.01978 |
| Sonnet 5 | $0.00035 | $0.00791 |
| Haiku 4.5 | $0.00018 | $0.00396 |
Grade A, and why
pm-vision-strategy 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Vision & Strategy Skill
How this skill behaves (read first)
This is a generative skill, and vision/strategy is where an AI assistant produces its most confident, least useful output. Two default failure modes dominate:
- The inspirational poster. Asked for a vision, Claude writes a buzzword sentence — "be the world's most loved, best-in-class platform that delights customers with seamless experiences" — that sounds good and guides zero decisions. If any feature can be justified by it, it's too vague to be a vision.
- Conflation and feature-listing. Claude treats vision, strategy, roadmap, and mission as interchangeable, and writes "strategy" as a list of features to build rather than a set of deliberate choices about where to play, how to win, and what not to do. Strategy that targets "everyone" and skips trade-offs isn't strategy.
A real vision is a specific, stable, user-centric destination; a real strategy is a focused set of interconnected, trade-off-driven choices grounded in evidence and tied to outcomes. So this skill gates:
- Establish context — vision, strategy, or both; company shape; product stage; market type; altitude.
- Apply the always-true core — the artifact distinctions, the laddering, the focus-and-trade-off discipline, the stability rule.
- Surface the context-dependent decisions (which framework, which communication format, portfolio/B2B/stage/depth) with trade-offs, and let the user choose. Running every framework at once is the failure mode.
Then it hands off to pm-okr-metric-validity-audit (the success metrics it names), pm-prioritization-rigor-audit (the themes/focus areas it sets, which drive what gets built), and pm-assumption-rigor-audit (the market-demand and competitive bets the strategy rests on).
Scope: this skill owns the vision artifact and the strategy artifact, and the choices inside them. It defers the competitive/market analysis that feeds strategy to pm-competitive-analysis, the research/insight-gathering to pm-discovery, problem framing to pm-problem-statement, the prioritization decision itself to pm-prioritization, the OKR/KPI artifacts to pm-okrs-kpis, the roadmap artifact and sequencing to pm-roadmap, pricing to ux-pricing, and go-to-market to pm-gtm-plan.
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 · 140 lines · 177 tokens per session scan A 89110b6fab41
pm-vision-strategy is a skill published in the GitHub repository Uxcel-Lab/product-skills (12 stars, last pushed 2mo ago), licensed MIT. It adds 177 tokens to every session and 3,956 once invoked, about $0.0009 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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