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 nWave-ai/nWave --skill nw-stakeholder-engagementgit clone --depth 1 https://github.com/nWave-ai/nWaveWrote 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/nwave-ai/nwave/nw-stakeholder-engagement)<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-stakeholder-engagement"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-stakeholder-engagement/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/nwave-ai/nwave/nw-stakeholder-engagement"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-stakeholder-engagement.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 | $0.00035 | $0.00726 |
| Opus 5.5 | $0.00014 | $0.00290 |
| Sonnet 5.5 | $0.00007 | $0.00145 |
| Haiku 4.5 | $0.00003 | $0.00073 |
Grade A, and why
nw-stakeholder-engagement 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 1mo 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stakeholder Engagement
Demonstration Preparation
Audience Analysis
Tailor presentation content and depth to audience type:
| Audience | Focus | Style | Success Criteria |
|---|---|---|---|
| Executive | Business value, ROI, strategic alignment | High-level outcomes, success metrics, roadmap | Business objective achievement, ROI demonstration |
| Business | Functional capability, process improvement, UX | Feature walkthrough, workflow demo, benefit realization | Requirement satisfaction, process efficiency |
| Technical | Implementation quality, architecture, ops readiness | Technical deep-dive, architecture review, operational metrics | Technical excellence, operational readiness |
Demonstration Script Development
Structure as problem-solution narratives:
- Before state: current pain point with quantitative evidence
- Feature walkthrough: end-to-end workflow with realistic data
- After state: measurable improvement with before/after comparison
- Business impact: translate technical metrics to business outcomes
Preparation Checklist
- Demo environment set up with realistic data
- Backup plan for demo failures (screenshots, recorded fallback)
- Stakeholder briefing sent with agenda and expectations
- Interactive participation points identified
- Time budget allocated per section
Feedback Collection
Structured Feedback Process
- Real-time feedback during demonstration (capture questions and concerns)
- Post-demonstration survey with structured questions
- Follow-up interviews for deeper insights (optional, for major features)
Feedback Categories
- Functional: does the feature meet requirements?
- Usability: is the user experience intuitive?
- Performance: does speed/responsiveness meet expectations?
- Priority: what enhancements should come next?
Feedback Action Workflow
- Categorize feedback items
- Prioritize by business impact
- Assign ownership for each action item
- Communicate response plan with timelines
- Track resolution to completion
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.
- 1mo ago First seen · 86 lines · 35 tokens per session scan A bb25100247f8
nw-stakeholder-engagement is a skill published in the GitHub repository nWave-ai/nWave (620 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 726 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 2026-09-06.
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