Modular skills for validating and using personnel selection procedures, derived from the SIOP/APA Principles for the Validation and Use of Personnel Selection Procedures (5th ed., 2018).
Use when preparing the administration documentation / manual for an operational selection procedure — the materials administrators and users need to administer, score, interpret, secure, and communicate the procedure consistently. Covers administrator qualifications, the testing environment, scoring/interpretation, security, candidate communications and feedback, reassessment, nonstandard administrations, data retention, and review/updating. Triggers: "administration manual", "test administration documentation", "test security", "candidate feedback", "retest policy", "reassessment", "data retention for test scores", "proctoring / unproctored internet testing".
Use when assessing candidates with disabilities or from different linguistic/ cultural backgrounds — deciding and documenting selection-procedure accommodations vs. modifications, preserving score comparability and construct measurement, and handling translation/adaptation. Covers the accommodation-vs- modification distinction, the candidate dialog, score handling, documentation, legal limits, and consistency with operational use. Triggers: "test accommodation", "disability accommodation", "modify a test", "extended time / Braille / screen reader", "construct-irrelevant barrier", "translate a test", "linguistic/cultural background", "ADA testing".
Use when building validity evidence by linking selection-procedure content to the work domain — demonstrating that the procedure samples important work behaviors, activities, and/or worker KSAOs defined by an analysis of work. Covers defining the content domain, SME qualifications and linkage judgments, sampling the domain, fidelity/specificity, competency-model foundations, and evaluating content evidence. Triggers: "content validity", "content-based strategy", "work sample", "job knowledge test", "link test content to the job", "SME linkage ratings", "no criterion data available".
Use when designing, conducting, or evaluating a criterion-related validity study — demonstrating an empirical relationship between selection-procedure (predictor) scores and work-relevant criteria. Covers predictive vs. concurrent designs, criterion development (relevance/contamination/deficiency/ reliability/bias), predictor choice, participant sampling, statistical power, data analysis, corrections for range restriction and unreliability, and combining predictors/criteria. Triggers: "criterion validity", "predictive/ concurrent study", "validity coefficient", "correct for range restriction", "criterion measure", "is the test related to performance".
Use when evaluating fairness and bias of a selection procedure — distinguishing the several meanings of "fairness," testing for predictive bias (differential prediction via moderated regression), and examining measurement bias (DIF, item sensitivity review). Covers what subgroup-mean differences do and don't imply, when bias analyses are warranted, and the statistical pitfalls. Triggers: "adverse impact vs bias", "differential prediction", "predictive bias", "measurement bias", "DIF analysis", "is the test fair / biased", "subgroup differences", "item sensitivity review".
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A library of modular, practitioner-oriented skills for Industrial-Organizational (I-O) psychologists. Each skill is a focused, self-contained unit of professional guidance grounded in authoritative professional standards, written so that an I-O psychologist (or an AI assistant supporting one) can pick up a single task in the employment-testing lifecycle without wading through a monolithic manual.
| Domain | Status | Source standard |
|---|---|---|
| Personnel Selection | ✅ Available | SIOP/APA Principles for the Validation and Use of Personnel Selection Procedures (5th ed., 2018) |
| AI Personnel Assessment | ✅ Available | Landers & Behrend (2023), Auditing the AI Auditors (American Psychologist) — extends Personnel Selection |
| AI Selection — Legal & Ethical Concerns | ✅ Available | Tippins, Oswald & McPhail (2021), Scientific, Legal, and Ethical Concerns About AI-Based Personnel Selection Tools (Personnel Assessment and Decisions) |
| Training & Development | ⬜ Planned | — |
| Performance Management | ⬜ Planned | — |
| Job/Work Analysis (standalone) | ⬜ Planned | — |
This repo is a Claude Code plugin marketplace. Each domain is a self-contained, independently
installable plugin; its skills live one level under that plugin's skills/ directory (the layout
Claude Code discovers).
<repo root>/
├── .claude-plugin/
│ └── marketplace.json ← lists the domain plugins below
├── <domain>/ ← one installable plugin per domain
│ ├── .claude-plugin/
│ │ └── plugin.json ← plugin manifest
│ ├── README.md ← domain index + recommended sequence
│ └── skills/
│ └── <skill-name>/
│ └── SKILL.md ← one focused task; YAML frontmatter + guidance
└── sources/ ← the source standards the skills are derived from
Each SKILL.md carries YAML frontmatter (name, description) in the
Claude Code Agent Skills format. Skill names are globally
unique, so cross-references between skills use the bare skill name (skills are invoked by name once
installed).
In Claude Code, add this marketplace, then install whichever domains you want:
/plugin marketplace add OpenMatter-Network/agent-io-skills
/plugin install personnel-selection@io-skills
/plugin install ai-personnel-assessment@io-skills
/plugin install ai-selection-legal-ethical@io-skills
Then /plugin marketplace update io-skills pulls future changes. (You can also use the
non-interactive CLI: claude plugin marketplace add OpenMatter-Network/agent-io-skills and
claude plugin install <name>@io-skills.) Skills are discovered automatically and invoked by name or
on demand; sources/ and the README files are documentation and are not loaded as skills.
These skills summarize and operationalize professional guidance for educational and practice-support
purposes. They are not legal advice and not a substitute for the source documents,
graduate training in validation, or licensed professional judgment. Always consult the primary
standard (sources/) and qualified counsel for high-stakes decisions.
Skills for auditing AI/ML personnel assessments for fairness, bias, validity, and utility, based on Landers & Behrend (2023), 'Auditing the AI Auditors.'
Skills for evaluating AI-based personnel selection tools against scientific, legal, and ethical standards, based on Tippins, Oswald & McPhail (2021), 'Scientific, Legal, and Ethical Concerns About AI-Based Personnel Selection Tools.'
npx claudepluginhub openmatter-network/agent-io-skills --plugin personnel-selectionUI/UX design intelligence. 67 styles, 161 palettes, 57 font pairings, 25 charts, 15 stacks (React, Next.js, Vue, Svelte, Astro, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui, Nuxt, Jetpack Compose). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, mobile app. Elements: button, modal, navbar, sidebar, card, table, form, chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, flat design. Topics: color palette, accessibility, animation, layout, typography, font pairing, spacing, hover, shadow, gradient.
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
This skill should be used when users need to generate ideas, explore creative solutions, or systematically brainstorm approaches to problems. Use when users request help with ideation, content planning, product features, marketing campaigns, strategic planning, creative writing, or any task requiring structured idea generation. The skill provides 30+ research-validated prompt patterns across 14 categories with exact templates, success metrics, and domain-specific applications.
Develop, test, build, and deploy Godot 4.x games with Claude Code. Includes GdUnit4 testing, web/desktop exports, CI/CD pipelines, and deployment to Vercel/GitHub Pages/itch.io.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
A growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.