Cognitive ux workflow
Skill kfeng209-oss/cognitive-ux/skills/cognitive-ux-workflow
Design and audit SaaS applications, internal tools, and recurring knowledge-work workflows using evidence-informed UX. Use when people repeatedly create, review, organize, approve, or resolve work; return an object/action model, primary and recovery flows, state/undo rules, accessible interaction requirements, and time-to-correct-outcome validation.From its SKILL.md
npx -y skills add kfeng209-oss/cognitive-ux --skill cognitive-ux-workflowAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
2.6 KB, 447 tokens by cl100k_base, as published. Nobody here has run it
Cognitive UX: Workflow SaaS
Scope
Use for product workflow surfaces. Use cognitive-ux-dashboard for data monitoring and cognitive-ux-admin for privileged administration.
Intake
- Identify user roles, objects, primary jobs, frequency, collaboration, and handoffs.
- Identify states, permissions, automation, irreversible outcomes, audit needs, and offline/error constraints.
- Identify existing mental models, device/input method, and success/failure measures.
State assumptions that could change the design. Define the primary task, its consequence of failure, and a measurable user outcome before proposing a layout.
Design procedure
- Model the product around user-recognizable objects, states, and actions; avoid exposing internal implementation vocabulary as the primary navigation.
- Map the happy path plus interruption, conflict, no-permission, empty, bulk, and recovery paths before choosing components.
- Keep system state visible; preserve context after filtering, sorting, navigation, async work, and automation.
- Use safe defaults, confirmation or undo for consequential changes, and specific error recovery without discarding work.
- Design automation as reviewable assistance with clear scope, status, provenance, and human override.
Read archetype evidence. Label each non-obvious recommendation Standard / requirement, Evidence-informed default, or Hypothesis to test.
Required outputs
- object/action/state model
- primary, exception, and recovery flow maps
- permission, automation, and undo/confirmation specification
- component behavior and accessibility checklist
- time-to-correct-outcome study
- Evidence-to-decision table: decision → mechanism → source → label → limitation → test metric.
- Accessibility, ethics, and recovery-path checklist.
Guardrails
Do not hide state changes, make destructive actions irreversible without warning, use modal sequences as a substitute for flow design, or automate beyond user authority.
Related skills
Use cognitive-ux-dashboard, cognitive-ux-onboarding, and cognitive-ux-admin. Select the primary task before combining skills; add a secondary skill only when it changes the user outcome or risk.
What ships with it: 2 files
1.4 KB alongside SKILL.md
agents/
- openai.yaml211 B
references/
- archetype-evidence.md1.2 KB