Prompt
1. Diagnostic Intake Flow
Core Interaction Flow (User Perspective)
1. User opens the tool during a moment of difficulty.
2. Instead of browsing dozens of strategies, they see a 20-second “What’s happening right now?” check-in.
3. User answers 4 rapid questions using taps and sliders.
4. Tool immediately calculates:
* Current regulation state
* Social support availability
* Time horizon
* Cognitive capacity
5. Tool routes directly to the best-matching strategy variant.
6. User lands on a ready-to-use strategy card.
No menus. No searching. No category browsing.
The system assumes that if someone is seeking executive function support, their executive function is already under load.
⸻
Diagnostic Questions
Question 1: Energy & Regulation
Prompt:
“How scrambled does your brain feel right now?”
Input:
5-point visual slider
Value Label
1 Steady
2 Slightly Frayed
3 Overloaded
4 Meltdown Approaching
5 Full Brain Fire Alarm
Stores:
regulation_level = 1-5
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Question 2: Social Context
Prompt:
“Who’s available right now?”
Input:
Large tap buttons
Options:
* Just me
* Someone nearby
* Group/class/team
* Not sure
Stores:
context = solo / partner / group / unknown
⸻
Question 3: Available Time
Prompt:
“How much time do you realistically have?”
Input:
Single tap buttons
Options:
* Under 2 minutes
* 5 minutes
* 15 minutes
* 30+ minutes
Stores:
time_window
⸻
Question 4: Cognitive Capacity
Prompt:
“What feels hardest right now?”
Input:
Single-select tiles
Options:
* Starting
* Choosing
* Remembering
* Staying focused
* Finishing
* Switching tasks
Stores:
target_function
⸻
Optional Question 5 (Adaptive)
Only appears if regulation ≥4.
Prompt:
“Do you need calm first?”
Options:
* Yes
* Maybe
* No
This prevents cognitive interventions from appearing when nervous system regulation should happen first.
⸻
Decision Logic
Every strategy variant contains metadata:
{
"strategy_id": "Goblin_Start_Button",
"base_function": "starting",
"contexts": ["solo","partner","group"],
"dysregulation_versions": true,
"minimum_time": 2,
"maximum_time": 15
}
Routing algorithm:
Step 1
Filter by target EF difficulty.
Example:
User selects:
“Starting”
Keep only strategies tagged:
starting
activation
task initiation
⸻
Step 2
Filter by time.
Example:
User has:
Under 2 Minutes
Remove strategies requiring >2 minutes.
⸻
Step 3
Filter by context.
Example:
Context = Solo
Prefer:
solo_variant
Fallback:
universal_variant
⸻
Step 4
Apply regulation override.
If:
regulation >= 4
AND strategy has dysregulation version:
Route to:
dysregulation_variant
instead of standard version.
⸻
Example
Inputs:
* Brain Fire Alarm
* Just Me
* Under 2 Minutes
* Starting
Output:
Not:
“Body Double Sprint”
Instead:
“Dysregulation Solo Version of Coin Quest Start”
because it:
* addresses initiation
* requires <2 minutes
* solo-compatible
* regulation-adapted
⸻
Intake Screen Wireframe
------------------------------------------------
HEADER
What's happening right now?
(20 second check-in)
------------------------------------------------
Q1 Regulation Slider
Steady ---------------- Fire Alarm
------------------------------------------------
Q2 Context
[ Just Me ]
[ Someone Nearby ]
[ Group ]
[ Not Sure ]
------------------------------------------------
Q3 Time
[ <2 min ]
[ 5 min ]
[ 15 min ]
[ 30+ min ]
------------------------------------------------
Q4 Hardest Thing
[ Starting ]
[ Choosing ]
[ Remembering ]
[ Focusing ]
[ Finishing ]
[ Switching ]
------------------------------------------------
CONTINUE BUTTON
[ Find My Strategy ]
------------------------------------------------
⸻
Rationale
Executive dysfunction often prevents users from accurately categorizing their needs into complex taxonomies.
Users identify current state rather than strategy type.
The system performs the classification work.
⸻
2. Dynamic Strategy Surfacing
Core Interaction Flow
1. User completes intake.
2. Recommendation engine scores all strategy variants.
3. Highest-scoring variant appears immediately.
4. User may:
* Start now
* View alternate recommendations
* Re-run intake
The default behavior is one recommendation.
Not ten.
Choice overload is intentionally reduced.
⸻
Matching Engine
Strategy Score Formula
Function Match = 40 points
Regulation Match = 25 points
Context Match = 20 points
Time Match = 15 points
Total = 100
⸻
Example
Strategy:
Floor Goblin Method
{
"function":"starting",
"context":"solo",
"regulation":"high",
"time":"2"
}
User:
{
"function":"starting",
"context":"solo",
"regulation":"5",
"time":"2"
}
Score:
40 + 25 + 20 + 15 = 100
Ranks #1
⸻
Recommendation Screen Wireframe
------------------------------------------------
YOUR BEST MATCH
⭐⭐⭐⭐⭐
Coin Quest Start
(Solo Dysregulation Version)
Why this was selected:
✓ You are overwhelmed
✓ Working alone
✓ Need to start
✓ Have less than 2 minutes
------------------------------------------------
[ Start Strategy ]
------------------------------------------------
Other Good Options
2. Floor Goblin
3. Dice Launch
4. Tiny Villain Monologue
------------------------------------------------
⸻
Rationale
Many EF systems fail because users must become librarians of their own toolkit.
This system acts as the librarian.
⸻
3. Quick-Reference Card + Embedded Progress Tracker
Core Interaction Flow
1. User opens strategy.
2. Instructions remain visible.
3. Progress tracker lives directly beneath each step.
4. User never switches screens.
5. Completion automatically opens reflection.
⸻
Strategy Card Structure
Header
Strategy Name
Difficulty Badge
Expected Duration
Context Badge
⸻
Steps
Example:
Step 1
Pick one visible object related to task.
□ Done
⸻
Step 2
Touch object.
□ Done
⸻
Step 3
Perform one action.
□ Done
⸻
Embedded Tracker
Located directly below instructions.
Options vary by strategy.
⸻
Tally Tracker
Actions Completed
[-] 3 [+]
⸻
Rating Tracker
Effort Required
⭐ ⭐ ⭐ ⭐ ⭐
⸻
Time Tracker
Start Timer
[ Start ]
Elapsed
2:13
⸻
Card Wireframe
------------------------------------------------
Coin Quest Start
2 Minute Strategy
Solo + Dysregulation
------------------------------------------------
STEP 1
Find one object connected to task.
[✓]
------------------------------------------------
STEP 2
Touch object.
[✓]
------------------------------------------------
STEP 3
Perform one tiny action.
[ ]
------------------------------------------------
Progress
Actions Completed
[-] 2 [+]
------------------------------------------------
Timer
02:13
------------------------------------------------
[ Done ]
------------------------------------------------
⸻
Rationale
Switching between instruction view and tracking view creates working-memory demands.
Measurement remains embedded inside action.
Users never need to remember where they are.
⸻
4. Outcome Logging & Personal Pattern Library
Core Interaction Flow
1. User finishes strategy.
2. One-screen reflection appears.
3. User answers 3 taps.
4. Session saved automatically.
5. Pattern Library updates.
No journaling required.
⸻
Logging Questions
Question 1
“Did this help?”
Buttons:
* Not Really
* A Little
* Yes
* Extremely
⸻
Question 2
“What changed?”
Multi-select
* I started
* I stayed focused
* I finished
* I calmed down
* Something else
⸻
Question 3
“Would you use this again?”
Thumbs Up / Neutral / Down
⸻
Stored Data
Each session:
{
"date",
"time",
"strategy",
"variant",
"regulation",
"context",
"time_available",
"target_function",
"outcome_rating",
"completion",
"duration"
}
⸻
Pattern Detection Examples
System calculates:
Success by Regulation State
Example:
Best strategy during high stress:
Coin Quest Start
Average rating: 4.7/5
⸻
Success by Time Window
Under 2 Minutes:
Floor Goblin
86% success
⸻
Context Trends
Group versions work 40%
better than solo versions.
⸻
Pattern Library Wireframe
------------------------------------------------
MY PATTERNS
------------------------------------------------
Top Helpers
1. Coin Quest Start
4.8 stars
2. Floor Goblin
4.6 stars
3. Dice Launch
4.5 stars
------------------------------------------------
When Overwhelmed
Best Strategy:
Coin Quest Start
Success Rate
92%
------------------------------------------------
Quick Wins
Under 2 Minutes
Floor Goblin
------------------------------------------------
Recent Sessions
June 18
★★★★★
Started Laundry
------------------------------------------------
⸻
Rationale
The user gradually builds externalized self-knowledge.
The system becomes a personalized executive-function field guide.
⸻
5. Offline-First Architecture
Core Interaction Flow
1. User opens app without internet.
2. Full toolkit remains available.
3. Intake still functions.
4. Recommendations still calculate.
5. Progress logging still saves.
6. Sync occurs automatically when online.
No dependency on connectivity.
⸻
Local Storage
Stored entirely on device:
Toolkit Database
strategies
variants
instructions
materials
tags
⸻
User Data
sessions
ratings
pattern metrics
favorites
history
⸻
Cached Analytics
success rates
recommendations
rankings
⸻
Sync Model
When internet returns:
Upload
* New sessions
* Ratings
* Pattern updates
Download
* Toolkit updates
* New strategy packs
* Bug fixes
⸻
Conflict Resolution
Newest timestamp wins.
For analytics:
Merge records.
Never overwrite logs.
⸻
Offline Wireframe Indicators
------------------------------------------------
⚡ Offline Mode
Everything still works.
7 sessions waiting to sync.
------------------------------------------------
[ Continue ]
------------------------------------------------
⸻
Constraints
Available Offline:
✅ Intake
✅ Recommendations
✅ Tracking
✅ Logging
✅ Pattern Library
Unavailable Offline:
❌ Cloud backup
❌ Cross-device sync
❌ Shared accountability features
❌ Live coaching integrations
⸻
Rationale
Executive function crises often occur:
* in cars,
* schools,
* workplaces,
* waiting rooms,
* rural areas,
* low-signal environments.
The tool must function at the exact moment support is needed, not when connectivity is available.
⸻
System-Level Transformation: From Toolkit to Decision-Support Engine
A traditional toolkit assumes the user can:
1. Recognize what problem they are experiencing.
2. Remember relevant strategies.
3. Search through options.
4. Compare variants.
5. Choose an intervention.
6. Execute it.
7. Track effectiveness.
Those seven steps are themselves executive function tasks.
This system removes most of them.
The user only identifies their current state:
* How overwhelmed am I?
* Who is available?
* How much time do I have?
* What feels hardest?
The system then performs the cognitive routing, selects the most appropriate strategy variant, embeds measurement directly within execution, captures outcomes automatically, and learns from repeated use.
Over time, the experience evolves from:
“Which strategy should I use?”
to
“Given how my brain works under these conditions, what has historically helped people like me, and especially me, right now?”
The static toolkit becomes a context-aware executive function copilot that adapts to the user’s cognitive state in real time rather than requiring the user to navigate the toolkit while already cognitively overloaded.