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-total-rewardsgit 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-total-rewards)<a href="https://agentmods.dev/skills/tuanductran/hr-skills/hr-total-rewards"><img src="https://agentmods.dev/badge/skills/tuanductran/hr-skills/hr-total-rewards/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-total-rewards"><img src="https://agentmods.dev/badge/skills/tuanductran/hr-skills/hr-total-rewards.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 | $0.00099 | $0.02940 |
| Opus 5 | $0.00049 | $0.01470 |
| Sonnet 5 | $0.00020 | $0.00588 |
| Haiku 4.5 | $0.00010 | $0.00294 |
Grade A, and why
hr-total-rewards 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 5d 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 — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.
HR total rewards
Comprehensive total rewards knowledge for HR managers, compensation analysts, benefits specialists, and total rewards leaders — from understanding modern compensation philosophy and market benchmarking to designing salary structures, benefits packages, and pay equity programs.
Supported tasks
- Explaining total rewards concepts and philosophy for HR teams and business leaders
- Designing salary structures, pay bands, and job leveling frameworks
- Benchmarking compensation against market data by role, level, and location
- Running pay equity analyses across gender, ethnicity, and level
- Designing incentive plans, bonus structures, and sales commission models
- Building equity compensation programs (stock options, RSUs, ESPPs)
- Designing benefits packages and evaluating benefits ROI
- Creating total rewards statements that communicate full compensation value
- Calculating compa-ratio, range penetration, and other compensation metrics
- Building compensation review and merit increase cycles
- Connecting total rewards strategy to retention and talent attraction goals
- Writing compensation philosophy documents, policies, and communication templates
What total rewards means in 2026
Modern total rewards is no longer:
- "just setting a salary number during an offer"
- "only running an annual merit increase cycle"
- "treating benefits as a fixed, unchanging cost line"
In 2026, modern total rewards increasingly includes:
- pay transparency driven by regulation and candidate expectation
- continuous market benchmarking rather than annual-only surveys
- skills-based and role-based pay structures replacing rigid title-based bands
- proactive pay equity analysis built into every compensation decision
- flexible and personalized benefits offerings
- total rewards statements that make hidden value visible to employees
- AI-assisted compensation modeling and scenario planning
- global and remote-work pay strategy spanning multiple geographies
Modern total rewards teams are increasingly expected to support:
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.
- 5d ago First seen · 343 lines · 99 tokens per session scan A f057cb21d6c6
hr-total-rewards is a skill published in the GitHub repository tuanductran/hr-skills (57 stars, last pushed 2d ago), licensed MIT. It adds 99 tokens to every session and 2,940 once invoked, about $0.0005 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 2026-09-07.
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