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Document a proposed integration's data needs, actions, credentials, and review boundaries.
Assess cognitive load across a complete multi-step process and produce a load map. Chains: cognitive-load-assessment, memory-load-reduction, wayfinding-navigation. Use when evaluating a checkout flow, onboarding sequence, application process, or any multi-step journey.
--- name: assess-load description: "Assess cognitive load across a complete multi-step process and produce a load map. Chains: cognitive-load-assessment, memory-load-reduction, wayfinding-navigation. Use when evaluating a checkout flow, onboarding sequence, application process, or any multi-step journey." --- # 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--- name: assess-load description: "Assess cognitive load across a complete multi-step process and produce a load map. Chains: cognitive-load-assessment, memory-load-reduction, wayfinding-navigation. Use when evaluating a checkout flow, onboarding sequence, application process, or any multi-step journey." --- # 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
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.