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 tuanductran/hr-skills --skill hr-ai-adoptiongit clone --depth 1 https://github.com/tuanductran/hr-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/tuanductran/hr-skills/hr-ai-adoption)<a href="https://agentmods.dev/skills/tuanductran/hr-skills/hr-ai-adoption"><img src="https://agentmods.dev/badge/skills/tuanductran/hr-skills/hr-ai-adoption/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/tuanductran/hr-skills/hr-ai-adoption"><img src="https://agentmods.dev/badge/skills/tuanductran/hr-skills/hr-ai-adoption.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 | $0.00073 | $0.00847 |
| Opus 5 | $0.00036 | $0.00424 |
| Sonnet 5 | $0.00015 | $0.00169 |
| Haiku 4.5 | $0.00007 | $0.00085 |
Grade A, and why
hr-ai-adoption 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI adoption in HR
Drive practical, sustained adoption of AI tools — among HR teams and the broader employee population — going beyond rollout announcements to build real usage, competence, and measurable impact.
Supported tasks
- Designing an AI adoption strategy for HR teams or the broader employee population
- Building enablement and training plans for new AI tool rollouts
- Identifying and addressing common sources of resistance to AI adoption
- Designing champion or early-adopter programs to drive peer-led adoption
- Measuring AI tool usage, adoption rates, and actual productivity impact
- Sequencing AI tool rollout to build momentum from early wins
- Communicating the "why" behind AI adoption in ways that reduce anxiety
- Addressing job security and role-change concerns tied to AI adoption
- Designing feedback loops to improve AI tools based on real usage
- Building manager enablement to support their teams through AI adoption
- Comparing adoption approaches for different AI tool types (chatbot, analytics, copilot)
- Sustaining adoption momentum after the initial rollout period fades
Key prompts
Strategy and planning
- "Design an AI adoption strategy for [HR team / broader employee population] rolling out [AI tool]."
- "Sequence the rollout of [AI tool] to build early momentum before expanding to the full population."
- "Design a champion or early-adopter program to drive peer-led adoption of [AI tool]."
- "What criteria should we use to decide which teams or functions get [AI tool] access first versus later in the rollout?"
Enablement and communication
- "Build an enablement and training plan to get [HR team] actually using [AI tool] day-to-day, not just aware of it."
- "Draft communication explaining why we're adopting [AI tool] in a way that reduces anxiety rather than increasing it."
- "How should managers be equipped to support their teams through adopting [AI tool]?"
- "Draft an FAQ document addressing the most common practical questions employees ask when [AI tool] is first introduced."
What ships with it
6 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.
- 12d ago First seen · 65 lines · 73 tokens per session scan A d5b002fdf842
hr-ai-adoption is a skill published in the GitHub repository tuanductran/hr-skills (57 stars, last pushed yesterday), licensed MIT. It adds 73 tokens to every session and 847 once invoked, about $0.0004 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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