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 aniganti/pm-superpowers --skill using-pm-superpowersgit clone --depth 1 https://github.com/aniganti/pm-superpowersWrote 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/aniganti/pm-superpowers/using-pm-superpowers)<a href="https://agentmods.dev/skills/aniganti/pm-superpowers/using-pm-superpowers"><img src="https://agentmods.dev/badge/skills/aniganti/pm-superpowers/using-pm-superpowers.svg" alt="Measured on agentmods" 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 | $0.00067 | $0.01037 |
| Opus 5 | $0.00034 | $0.00518 |
| Sonnet 5 | $0.00013 | $0.00207 |
| Haiku 4.5 | $0.00007 | $0.00104 |
Grade A, and why
using-pm-superpowers 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 8d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Using PM Superpowers
You are the guide to the PM Superpowers plugin. When invoked, help the PM understand what skills are available, how they connect, and which one to use for their current need.
Available Skills
| Skill | What It Does | Best For |
|---|---|---|
| strategy | Interactive 6-step product strategy framework (Rumelt's kernel) | Building a comprehensive product strategy from scratch or reviewing an existing one |
| competitive-landscape | Competitor profiling, positioning maps, whitespace identification | Understanding your competitive environment and finding opportunities |
| vrio-analysis | Assess resources/capabilities for sustained competitive advantage | Evaluating which internal strengths are truly defensible |
| strategic-moat | Defensibility assessment across 8 moat types | Understanding how defensible your product is and how to deepen moats |
| product-ecosystem | Value chain mapping, integration opportunities, portfolio coherence | Analyzing your product's position in the broader ecosystem |
| pre-mortem | Risk analysis with Tigers/Paper Tigers/Elephants framework | Stress-testing a product launch or major initiative before it ships |
| prompt-builder | Guided AI prompt creation through 9 structured questions | Crafting effective prompts for any AI tool |
| verification | Quality check on any strategy artifact before sharing | Ensuring your documents are complete, consistent, and ready for stakeholders |
| stakeholder-alignment | Tailored briefing docs, FAQs, and workshop agendas per audience | Preparing to present strategy to different stakeholder groups |
| decision-log | Structured capture of product decisions with reasoning | Building institutional memory and preventing re-litigation of settled decisions |
| prioritization | Framework-driven feature/initiative prioritization (RICE, ICE, weighted scoring) | Ranking a backlog of features or initiatives with evidence-based scoring |
Recommended Workflows
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.
- 8d ago First seen · 96 lines · 67 tokens per session scan A edd0b943646c
using-pm-superpowers is a skill published in the GitHub repository aniganti/pm-superpowers (47 stars, last pushed 24d ago), licensed MIT. It adds 67 tokens to every session and 1,037 once invoked, about $0.0003 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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