Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
owl-listener avatar

Assess Load

  • 35 installs
  • 87 repo stars
  • Updated June 9, 2026
  • owl-listener/inclusive-design-skills

Helps with ai & agent building tasks during AI-assisted development.

About

assess-load is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.

  • assess-load
  • AI & Agent Building
  • AI-coding skill

Assess Load by the numbers

  • 35 all-time installs (skills.sh)
  • +5 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #8,740 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/owl-listener/inclusive-design-skills --skill assess-load

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs35
repo stars87
Last updatedJune 9, 2026
Repositoryowl-listener/inclusive-design-skills

What it does

Helps with ai & agent building tasks during AI-assisted development.

Files

SKILL.mdMarkdownGitHub ↗

Assess Load

Map the cognitive load across a complete multi-step process and identify where users are most likely to struggle, give up, or make errors.

Process

Step 1: Map the Journey

List every step in the process from start to completion. For each step, note: what the user sees, what they must do, and what they must decide.

Step 2: Rate Each Step

Using cognitive-load-assessment, evaluate each step across all six dimensions (decisions, memory, concepts, steps, reading, visual). Record the rating for each.

Step 3: Identify Load Spikes

Plot the load across the journey. Identify:

  • Steps where load suddenly increases (load spikes)
  • Consecutive steps with medium-or-higher load (sustained load)
  • Points where users must remember information from earlier steps

(memory bridges)

Step 4: Check Navigation and Memory

Using wayfinding-navigation and memory-load-reduction, verify:

  • Can users always get back to a previous step?
  • Is progress saved automatically?
  • Is key context carried forward between steps?
  • Can users see where they are in the overall process?

Step 5: Recommendations

For each load spike or sustained load zone, recommend specific design changes to bring the load rating down.

Output

Deliver a cognitive load map: a step-by-step table showing the load rating at each point in the journey, annotated with:

  • Load spikes flagged in red
  • Memory bridges highlighted
  • Specific reduction recommendations for each issue
  • An overall cognitive load score for the process

Related skills

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.