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 agentmods add skills/jayrha/agentskills/job-description-writernpx skills add JayRHa/AgentSkills --skill job-description-writergit clone --depth 1 https://github.com/JayRHa/AgentSkillsWrote 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/jayrha/agentskills/job-description-writer)<a href="https://agentmods.dev/skills/jayrha/agentskills/job-description-writer"><img src="https://agentmods.dev/badge/skills/jayrha/agentskills/job-description-writer.svg" alt="Measured on agentmods" 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 | $0.00107 | $0.01579 |
| Opus 5 | $0.00053 | $0.00790 |
| Sonnet 5 | $0.00021 | $0.00316 |
| Haiku 4.5 | $0.00011 | $0.00158 |
Grade A, and why
job-description-writer 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Job Description Writer
Overview
Keywords: job description, JD, job posting, job ad, role, hiring, recruiting, responsibilities, requirements, qualifications, inclusive hiring, salary range, level, seniority, EEO, talent acquisition.
This skill produces job descriptions that attract qualified, diverse candidates and accurately represent the role. A strong JD does three jobs at once: it markets the role and company, it filters for fit (without over-filtering), and it sets expectations for the first year. The most common failure modes are inflated requirement lists that deter qualified candidates (especially underrepresented groups), vague responsibilities that describe activity instead of outcomes, and biased or coded language.
Always optimize for: clarity, inclusivity, accuracy, and measurable impact.
Workflow
-
Gather inputs. Collect the essentials before writing. If the user hasn't provided them, ask concise clarifying questions (batch them). Minimum needed: job title, level/seniority, team & reporting line, top 3-5 outcomes the hire owns, location/remote policy, employment type, and any compensation data. See
references/intake-questions.mdfor the full checklist. -
Define outcomes first, then responsibilities. Before listing duties, write what success looks like at 30/90/365 days. Convert each outcome into 5-8 responsibility bullets phrased as ownership ("Own X", "Drive Y", "Ship Z") rather than activity ("Responsible for attending meetings").
-
Split requirements into Must-have vs. Nice-to-have. Keep must-haves to 4-7 genuinely non-negotiable items. Everything aspirational goes under nice-to-have. Strip proxy requirements (degree, exact years) unless legally or functionally essential. See
references/inclusive-language.mdfor substitutions. -
Add impact + level context. State why the role exists, who it affects, and how performance is measured. Calibrate scope language to the level (see the leveling table below).
What ships with it
5 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 · 89 lines · 107 tokens per session scan A d150f0f7b199
job-description-writer is a skill published in the GitHub repository JayRHa/AgentSkills (4 stars, last pushed 1mo ago), licensed MIT. It adds 107 tokens to every session and 1,579 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 2026-08-31.
Other skills, from other repositories
reverse-engineering-tools
Guide for reverse engineering protected games and anti-cheat components across user mode, kernel mode, and hypervisor-aware environments. Use this skill when analyzing drivers, IOCTL protocols, callback registration, injected-code artifacts, integrity checks, protected binaries, or debugging security-sensitive game…
frontend-patterns
Frontend development patterns for React, Next.js, state management, performance optimization, and UI best practices.
codex-skin-pack-installer
Install Codex themes and Codex skin packs with npx skills. Use this skill when a user wants Codex to find, download, validate, apply, switch, remix, or restore Codex desktop themes such as caishen-readable, caishen-lite, mythic-guardian-noir, global-founder-bright, export-night, or caishen-max. It stages verified…
browser-qa
自动化视觉测试与 UI 交互验证。部署功能后使用浏览器自动化验证关键页面、核心路径和发布前回归。 当任务需要真实浏览器验证渲染、导航、交互或前端上线风险时使用。.
eval-harness
正式评估框架，实现 eval-driven development (EDD) 原则。 用于定义 pass/fail 标准、测量 pass@k 指标、创建回归测试套件。.
launchfast-product-research
Codex-native multi-keyword Amazon opportunity scan using LaunchFast MCP. Use when the user wants to research 1-10 keywords, compare niches, or decide whether a product idea is a GO, INVESTIGATE, or PASS. Requires the LaunchFast MCP tool researchproducts.