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-change-managementgit 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-change-management)<a href="https://agentmods.dev/skills/tuanductran/hr-skills/hr-ai-change-management"><img src="https://agentmods.dev/badge/skills/tuanductran/hr-skills/hr-ai-change-management/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-change-management"><img src="https://agentmods.dev/badge/skills/tuanductran/hr-skills/hr-ai-change-management.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 | $0.00078 | $0.01047 |
| Opus 5 | $0.00039 | $0.00524 |
| Sonnet 5 | $0.00016 | $0.00209 |
| Haiku 4.5 | $0.00008 | $0.00105 |
Grade A, and why
hr-ai-change-management 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI change management for HR
Lead the human side of AI adoption — from assessing workforce AI readiness and designing targeted communication strategies to managing resistance, building AI skills, and creating a culture that embraces AI as a productivity partner rather than a threat.
Supported tasks
- Assessing workforce AI readiness and adoption barriers
- Designing AI change management strategies and plans
- Communicating AI changes to employees at all levels
- Managing fear, resistance, and anxiety about AI and automation
- Designing AI reskilling and upskilling programs for non-technical employees
- Building manager capability to lead their teams through AI transitions
- Creating AI adoption metrics and change health indicators
- Designing AI ambassador and champion programs
- Facilitating AI impact assessments for specific roles and teams
- Building AI fluency across the non-technical workforce
- Connecting AI change management to workforce transformation strategy
- Supporting leaders in modeling positive AI adoption behaviors
Key prompts
AI readiness assessment
- "Assess our workforce's AI readiness across [departments] using [survey / focus group / data analysis] methods."
- "What factors predict whether employees will embrace or resist AI adoption in [company context]?"
- "Design an AI readiness survey for [employee population] that identifies adoption barriers and enablers."
- "How do we segment our workforce by AI readiness level and design targeted change strategies for each segment?"
- "What signals indicate that AI adoption resistance is becoming an organizational risk that needs urgent attention?"
Change communication for AI
- "Design an AI adoption communication strategy for [company] covering key messages, channels, and timeline."
- "Write an all-company communication announcing [AI tool adoption] that addresses employee concerns about job security honestly."
- "What messaging resonates with [operations / technical / administrative] employees who are anxious about AI replacing their roles?"
- "Write a manager guide for having 1:1 conversations with team members who are worried about AI."
- "How do we communicate AI changes transparently without creating unnecessary alarm or false reassurance?"
- "Design a multi-stage communication plan for [AI transformation initiative] from announcement through adoption."
What ships with it
3 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 · 78 lines · 78 tokens per session scan A 4009139963fb
hr-ai-change-management is a skill published in the GitHub repository tuanductran/hr-skills (57 stars, last pushed 2d ago), licensed MIT. It adds 78 tokens to every session and 1,047 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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