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-job-analysisgit 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-job-analysis)<a href="https://agentmods.dev/skills/tuanductran/hr-skills/hr-job-analysis"><img src="https://agentmods.dev/badge/skills/tuanductran/hr-skills/hr-job-analysis/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-job-analysis"><img src="https://agentmods.dev/badge/skills/tuanductran/hr-skills/hr-job-analysis.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 | $0.00077 | $0.01051 |
| Opus 5 | $0.00039 | $0.00526 |
| Sonnet 5 | $0.00015 | $0.00210 |
| Haiku 4.5 | $0.00008 | $0.00105 |
Grade A, and why
hr-job-analysis 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 9d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Job analysis and job content design
Conduct rigorous job analysis and design accurate job content — from gathering task and competency data and documenting job requirements to evaluating job complexity, supporting job classification decisions, and connecting job analysis to compensation and workforce planning.
Supported tasks
- Planning and conducting structured job analysis projects
- Designing job analysis interviews and questionnaires
- Documenting job tasks, duties, and responsibilities
- Defining knowledge, skills, abilities, and other requirements (KSAOs)
- Conducting task analysis for training needs assessment
- Evaluating job complexity for job classification and banding decisions
- Supporting FLSA and labor law classification decisions
- Designing job analysis frameworks for new role families
- Connecting job analysis to competency frameworks and job architectures
- Running job audits to validate whether job content reflects actual work
- Using job analysis data for workforce planning and skills gap analysis
- Building defensible job content documentation for legal compliance
Key prompts
Job analysis planning and methods
- "Design a job analysis plan for [role or role family] including methods, data sources, and stakeholders."
- "What job analysis methods are most appropriate for [technical / managerial / operational] roles?"
- "How do we conduct a rapid job analysis when we need job content documentation quickly?"
- "Design a job analysis interview guide for gathering task and requirement data from [incumbents / supervisors]."
- "What questionnaire design principles produce reliable, complete job analysis data?"
- "How do we validate job analysis data to ensure it reflects actual work, not idealized work?"
Job content documentation
- "Write the job content for a [role title] including essential duties, task frequency, and time allocation."
- "Document the knowledge, skills, abilities, and other requirements (KSAOs) for [role title]."
- "How do we distinguish between essential and marginal job functions for [role] for ADA compliance purposes?"
- "Write a comprehensive job content summary for [role] that can be used for job evaluation, hiring, and performance management."
- "How do we document the job requirements for a role that varies significantly across different work settings?"
What ships with it
4 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.
- 9d ago First seen · 77 lines · 77 tokens per session scan A 93e244903a05
hr-job-analysis is a skill published in the GitHub repository tuanductran/hr-skills (58 stars, last pushed today), licensed MIT. It adds 77 tokens to every session and 1,051 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 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…