human-computer-interaction

Human-computer interaction (HCI) as a discipline -- usability heuristics, interaction paradigms (CLI, GUI, touch, voice, gesture, spatial), accessibility, cognitive load theory, Fitts's law, user research methods, and the evolution of interfaces from punchcards to spatial computing. Use when evaluating interface usability, choosing interaction paradigms, applying accessibility standards, or understanding why some interfaces work and others fail. Broader than design-thinking -- this skill covers the science of how humans and computers communicate.

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リポジトリ: Tibsfox/gsd-skill-creator
ソースの最終更新活動: 2026年4月14日 07:57
検出された SKILL.md の言語: 英語
スター: 69
フォーク: 9

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npx skills add https://github.com/Tibsfox/gsd-skill-creator --skill human-computer-interaction

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goal-ambiguity-gate

Use the moment a request is underspecified and you are about to act on an ASSUMED goal. Enumerate the candidate goals the request could mean, project the action or artifact each one implies, and check whether they diverge: if two or more plausible goals lead to materially different actions or artifacts, ask exactly ONE targeted clarifying question; otherwise proceed on the most-likely goal and state the assumption in one line. Clarification is an evidence-producing action, not a delay — but one question, never an interrogation. Distinct from gsd-spec-phase (GSD-phase-bound, emits a heavy SPEC.md) and intent-router (fetch strategy, not goal disambiguation). Backed by agent goal-state inference (arxiv 2606.16813v1). Triggers on acting under an assumed goal when the request admits more than one materially different reading.

2026-07-19

memory-hubness-gate

Use at write time to vector/embedding memory — Grove content-addressed insertion, chroma/pgvector upserts, memory-consolidation promoting session traces to MEMORY.md, or embedding externally-ingested content. Scores each candidate record against a fixed panel of sentinel queries and quarantines any record that would become the nearest neighbor of too many unrelated queries — a hub — whether from adversarial poisoning or accidental over-generality. This is the memory-record-side sibling of skill-injection-guardian (file-side) and the write-side complement of memory-use-warrant (read-side). Quarantine, never silently drop; a human reviews. Backed by the admission-time hubness gate (arxiv 2606.19692v1). Triggers on inserting into vector memory, consolidating memory, and embedding stranger content.

2026-07-19

memory-use-warrant

Run this appropriateness check the moment you are about to integrate a retrieved long-term memory — a Grove content-addressed hit, a chroma/pgvector neighbour, a memory-consolidation digest, or a MEMORY.md line — into a response, especially anything touching private origins, Fox Companies IP, credentials, or Center Camp / consent-governed content. It answers a question intent-router never asks: not WHAT to fetch or HOW, but WHETHER a correctly-retrieved item should reach output. Relevance is not appropriateness — a perfect similarity match can still be a boundary violation. Default is FAIL-CLOSED: if in-context authorization is uncertain, the memory may inform behaviour but must not be surfaced. Backed by RBI-Eval (arxiv 2606.06055v1). Triggers on surfacing recalled sensitive memory into a response.

2026-07-19

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name	human-computer-interaction
description	Human-computer interaction (HCI) as a discipline -- usability heuristics, interaction paradigms (CLI, GUI, touch, voice, gesture, spatial), accessibility, cognitive load theory, Fitts's law, user research methods, and the evolution of interfaces from punchcards to spatial computing. Use when evaluating interface usability, choosing interaction paradigms, applying accessibility standards, or understanding why some interfaces work and others fail. Broader than design-thinking -- this skill covers the science of how humans and computers communicate.
type	skill
category	technology
status	stable
origin	tibsfox
modified	false
first_seen	"2026-04-12T00:00:00.000Z"
first_path	examples/skills/technology/human-computer-interaction/SKILL.md
superseded_by	null

Human-Computer Interaction

Human-computer interaction (HCI) is the study of how people use computers and how computers can be designed to be useful and usable. It draws on computer science, cognitive psychology, design, and sociology. This skill covers the science behind good interfaces: why some are intuitive and others are hostile, how human cognition constrains interface design, and how interaction paradigms have evolved.

Agent affinity: norman (HCI founder, affordances, usability heuristics), resnick (creative learning interfaces, constructionism), borg (accessible and equitable systems)

Concept IDs: tech-computer-architecture, tech-software-concepts, tech-design-brief

Part I -- Interaction Paradigms

A Brief History

Era	Paradigm	Input	Users
1950s-60s	Batch processing	Punch cards, paper tape	Specialists
1960s-70s	Command-line interface (CLI)	Keyboard	Technical professionals
1970s-80s	Graphical user interface (GUI)	Mouse + keyboard	General public (Xerox PARC, Mac, Windows)
2000s	Touch	Fingers on screen	Everyone (iPhone, 2007)
2010s	Voice	Speech	Hands-free contexts (Siri, Alexa)
2020s	Spatial / Mixed reality	Gesture, gaze, voice	Emerging (AR/VR headsets)
2020s	Conversational AI	Natural language text	Emerging (chatbots, LLM interfaces)

Each new paradigm does not replace the previous ones. CLIs remain essential for system administration. GUIs dominate productivity work. Touch dominates mobile. The right paradigm depends on the context, not the era.

Choosing an Interaction Paradigm

Factor	Favors
Precision and repeatability	CLI (scriptable, exact)
Discoverability and exploration	GUI (visible options)
Mobility and casual use	Touch (portable, no peripherals)
Hands-busy contexts	Voice (cooking, driving)

Principle	Meaning	Examples
Perceivable	Users can perceive the content	Alt text for images, captions for video, sufficient contrast
Operable	Users can interact with the interface	Keyboard navigation, sufficient time, no seizure triggers
Understandable	Users can understand the content	Clear language, predictable behavior, error guidance
Robust	Content works with assistive technologies	Semantic HTML, ARIA labels, standards compliance

Method	Stage	Data type	Best for
Contextual inquiry	Early (empathy)	Qualitative	Understanding current practices
Card sorting	Early (information architecture)	Qualitative + quantitative	Organizing content categories
Usability testing	Mid (prototype)	Qualitative + quantitative	Finding interaction problems
A/B testing	Late (production)	Quantitative	Optimizing specific metrics
Analytics	Ongoing	Quantitative	Understanding real usage patterns
Surveys	Any	Quantitative	Measuring satisfaction at scale
Diary studies	Longitudinal	Qualitative	Understanding behavior over time

human-computer-interaction

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Human-Computer Interaction

Part I -- Interaction Paradigms

A Brief History

Choosing an Interaction Paradigm

Human-Computer Interaction

Part I -- Interaction Paradigms

A Brief History

Choosing an Interaction Paradigm

Part II -- Usability Heuristics

Nielsen's 10 Usability Heuristics (1994)

Applying Heuristics

Part III -- Cognitive Foundations

Cognitive Load Theory

Fitts's Law

Hick's Law

Recognition vs Recall

Part IV -- Accessibility

Why Accessibility Matters

WCAG Principles (POUR)

Assistive Technologies

Part V -- User Research Methods

Cross-References

References

human-computer-interaction

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このリポジトリの他の Skills

このリポジトリの他の Skills

Human-Computer Interaction

Part I -- Interaction Paradigms

A Brief History

Choosing an Interaction Paradigm

Human-Computer Interaction

Part I -- Interaction Paradigms

A Brief History

Choosing an Interaction Paradigm

Part II -- Usability Heuristics

Nielsen's 10 Usability Heuristics (1994)

Applying Heuristics

Part III -- Cognitive Foundations

Cognitive Load Theory

Fitts's Law

Hick's Law

Recognition vs Recall

Part IV -- Accessibility

Why Accessibility Matters

WCAG Principles (POUR)

Assistive Technologies

Part V -- User Research Methods

Cross-References

References