System: MWMS
Document Type: Framework
Authority Level: MCR Source Of Truth
Status: Draft For MCR
Primary Location: MCR
Future Operational Destination: HeadOffice Brain, AI Business Systems Brain, AI Manager, AI Employee Router, Brain Room, Course Absorption System, Content Brain, Offer Brain, Sales Brain, Creative Brain, Research Brain, Future AIBS Client Systems
Parent Page: HeadOffice
Owner: Martyn
Developer Boundary: No Development Action Authorized By This Page
Source Of Truth: MCR
Purpose
The purpose of this document is to define the MWMS AI Skill Brainstorm And Prioritization Framework.
This framework establishes how MWMS identifies, evaluates, ranks, parks, rejects, and prioritizes possible AI skills before investing time into building them.
MWMS must not build AI skills just because an idea sounds useful.
A skill should exist because it solves a repeated operational problem, improves output quality, reduces drift, supports a Brain, or creates a reusable workflow for MWMS or future AIBS client systems.
Without a prioritization framework, MWMS risks:
creating too many skills
creating vague skills
building skills that are rarely used
duplicating existing procedures
building skills before context exists
turning every task into a skill
confusing skill ideas with AI Employee roles
creating client skills before client workflows are understood
adding unnecessary maintenance burden
The AI Skill Brainstorm And Prioritization Framework ensures that skill creation remains selective, useful, and aligned with the MWMS ecosystem.
Scope
This framework applies to all MWMS skill ideation, skill selection, skill prioritization, and skill backlog decisions.
This includes:
HeadOffice Brain
AI Business Systems Brain
AI Manager
AI Employee Router
Brain Room
Course Absorption System
Newsletter Intelligence
Opportunity System
Content Brain
Offer Brain
Creative Brain
Sales Brain
Conversion Brain
Customer Brain
Research Brain
Affiliate Brain
Ads Brain
Operations Brain
future AIBS client systems
This framework applies when MWMS is deciding whether to create skills for:
course absorption
newsletter processing
offer evaluation
content planning
creative strategy
ad scripting
sales follow-up
client reporting
context library building
voice checking
proof review
developer handoff preparation
client onboarding
research synthesis
asset creation
audit and decay prevention
This framework does not authorize development work, plugin changes, Supabase changes, WordPress changes, automation wiring, tool access, or M developer action.
Core Definition
AI Skill Brainstorming is the process of identifying possible repeated tasks that may become reusable AI skills.
AI Skill Prioritization is the process of deciding which skill ideas should be built now, updated, merged, parked, rejected, or saved for later.
A skill idea is not the same as a skill.
A skill idea becomes a skill only after it passes the required tests and has enough clarity to define input, context, procedure, output, validation, and handoff.
Core Principle
The core principle of this framework is:
Build the skills that reduce repeated friction, protect quality, and support real MWMS workflows first.
MWMS should prioritize skills that:
save repeated explanation
reduce human correction
protect governance
improve output consistency
support active Brains
support current workflows
protect client systems
reduce risk
increase business usefulness
A skill that sounds clever but does not support real work should be parked or ignored.
Skill Brainstorm Sources
MWMS may identify possible skill ideas from several sources.
Repeated User Requests
If Martyn repeatedly asks for the same type of output, a skill may be needed.
Examples:
full page output
course absorption block review
developer handoff
newsletter intelligence extraction
tomorrow task list
Repeated Corrections
If Martyn repeatedly corrects the same failure, a skill or skill update may be needed.
Examples:
wrong page format
too much summary
missing MCR structure
vague developer instructions
citations inside copy-paste pages
Repeated Workflows
If MWMS performs the same workflow often, a skill may be useful.
Examples:
offer evaluation
content brief creation
context library construction
voice checking
proof review
Course Absorption
If course material reveals a strong repeatable method, a skill may be considered.
Examples:
lead magnet builder
webinar builder
content scanner
skill audit
Client Needs
Future AIBS clients may reveal repeated tasks that can become client-specific skills.
Examples:
client report drafting
client content planning
client sales reply drafting
client support reply structuring
System Failures
If a workflow fails repeatedly, a skill may be needed to standardize it.
Examples:
missing validation
wrong Brain routing
poor handoff
forgotten context
wrong output destination
Business Opportunity
If a skill could become part of a future AIBS client package, it may be prioritized.
Examples:
Client IP Excavator
Context Library Builder
Voice Checker
Client Report Drafting Skill
Skill Brainstorm Questions
Use these questions when brainstorming skill ideas.
- What work does MWMS repeat often?
- What work does Martyn keep asking for?
- What work keeps needing correction?
- What work depends on MWMS-specific rules?
- What work would be risky if done generically?
- What work requires context files?
- What work requires a repeatable output format?
- What work could future AI Employees perform?
- What work could future AIBS clients need?
- What work should not become a skill yet?
- What work needs human judgment and should stay manual?
- What work already has an existing skill or standard?
Skill Idea Capture Template
Each brainstormed skill idea should be captured using the following structure.
Skill Idea Name:
Proposed Owning Brain:
Possible AI Employee:
Task Repeated:
Current Pain Or Friction:
Input Required:
Context Required:
Possible Output:
Workflow Supported:
Business Value:
Risk Level:
Existing Related Skill Or Standard:
Should Build Now:
Should Merge:
Should Park:
Should Reject:
Notes:
Minimum Skill Idea Capture
For quick capture, use:
Skill Idea:
Why It Matters:
Owning Brain:
Input:
Output:
Priority:
Next Decision:
Skill Prioritization Tests
MWMS uses several tests before building a skill.
Test 1: Repetition Test
Does this task happen repeatedly?
If no, do not build a skill yet.
Test 2: Specific Method Test
Does MWMS have a specific way of doing this task?
If no, define the method first.
Test 3: Drift Risk Test
Would AI likely do this incorrectly without guidance?
If yes, the skill may be valuable.
Test 4: Context Dependency Test
Does the task require specific context files or standards?
If yes, skill structure may help.
Test 5: Output Clarity Test
Can the output be clearly defined?
If no, the skill is not ready.
Test 6: Validation Test
Can MWMS check whether the skill worked?
If no, do not operationalize yet.
Test 7: Business Value Test
Does this skill improve MWMS operations, revenue potential, client delivery, quality, speed, safety, or scalability?
If no, park or reject.
Test 8: Duplication Test
Does an existing skill, standard, framework, or protocol already cover this?
If yes, update or merge instead of creating a new skill.
Test 9: Risk Test
Could this skill cause risk if used incorrectly?
If yes, human review and strict boundaries are required.
Test 10: Timing Test
Is this skill useful now, or is it premature?
If premature, park it.
Skill Priority Levels
MWMS uses the following priority levels.
Priority 1: Build Now
Skill supports an active workflow, repeated friction, high-value output, or current system need.
Priority 2: Build Soon
Skill is valuable but not urgent.
Priority 3: Park For Later
Skill may be useful later but is premature.
Priority 4: Merge Or Update Existing Skill
Skill idea overlaps an existing skill or standard.
Priority 5: Reject
Skill is too vague, low value, duplicated, risky, or unnecessary.
Priority 6: Needs More Context
Skill may be useful, but input, output, workflow, or owner is unclear.
Skill Prioritization Score
MWMS may score each skill idea across six areas.
Repetition Score
How often does the task happen?
1 = rarely
5 = constantly
Friction Score
How much pain, correction, or inefficiency exists?
1 = minor
5 = major
Business Value Score
How much value does the skill create?
1 = low
5 = high
Drift Risk Score
How likely is generic AI to get it wrong?
1 = low
5 = high
Clarity Score
How clear are input, procedure, and output?
1 = unclear
5 = very clear
Timing Score
How useful is the skill now?
1 = premature
5 = needed now
High-priority skills usually score high in repetition, friction, business value, drift risk, clarity, and timing.
Skill Backlog Categories
MWMS should maintain a skill backlog with clear categories.
Build Now
Ready for skill creation.
Build Soon
Useful but not immediate.
Needs Method First
Task repeats but procedure is not clear enough.
Needs Context First
Task requires context files that do not yet exist.
Merge Candidate
Should update or merge with an existing skill.
Client-Specific Candidate
Useful for future AIBS clients but not general MWMS yet.
Automation Candidate Later
May become automated after manual use is proven.
Parked
Not needed now.
Rejected
Should not be built.
Build Now Criteria
A skill should be built now when:
the task repeats
the method is known
the input is clear
the output is clear
the owning Brain is clear
the context requirement is clear
the skill reduces repeated correction
the skill supports active MWMS work
the skill can be validated
the timing is right
Examples of Build Now skills may include:
Course Absorption Evaluation Skill
MCR Full Page Output Skill
Developer Handoff Precision Skill
Context Library Builder Skill
Voice Checker Skill
Proof Review Skill
Park For Later Criteria
A skill should be parked when:
the idea is useful but premature
the owning Brain is not ready
the workflow is not active yet
the client use case is future-only
the context library does not exist yet
the procedure is not clear enough
the output is not defined
the business need is not immediate
Reject Criteria
A skill should be rejected when:
the task does not repeat
the skill duplicates existing material
the idea is too vague
the output cannot be validated
the task is low value
the task should remain human judgment
the skill would increase system clutter
the skill creates risk without enough benefit
Merge Criteria
A skill idea should merge into an existing skill when:
same workflow
same input
same output
same owning Brain
same validation
same handoff
only small procedure improvement needed
Do not create new skills for minor variations.
Split Criteria
A skill idea should be split when:
it covers too many tasks
it has multiple outputs
it crosses too many Brains
it includes both strategy and execution
it includes both creation and validation
it has conflicting trigger conditions
Large skills create drift.
Smaller precise skills are easier to govern.
Skill Brainstorm Workflow
MWMS uses the following workflow.
Step 1: Capture Skill Ideas
List potential skills without judging too early.
Step 2: Group Similar Ideas
Cluster overlapping skill ideas.
Step 3: Identify Repeated Workflows
Mark which ideas solve repeated tasks.
Step 4: Identify Existing Standards
Check whether existing frameworks or skills already cover the idea.
Step 5: Apply Prioritization Tests
Use repetition, method, drift, context, output, validation, business value, duplication, risk, and timing tests.
Step 6: Assign Priority
Build Now, Build Soon, Park, Merge, Reject, Needs Context, or Needs Method.
Step 7: Define Next Action
For each skill idea, record what happens next.
Step 8: Review Backlog Periodically
Remove stale ideas and promote useful ones when timing changes.
Skill Backlog Review
MWMS should review skill backlog periodically.
Review questions:
Is this skill still needed?
Has the workflow become active?
Has the context now been created?
Has the method become clearer?
Has another skill replaced it?
Is this still worth building?
Should this be merged?
Should this be retired from the backlog?
Does this support future AIBS client packaging?
Backlog review prevents skill clutter.
Examples
Example 1: Full Page Output Skill
Repeated Task:
Martyn asks for copy-paste-ready MCR pages.
Friction:
Previous output failed format expectations.
Business Value:
High.
Drift Risk:
High.
Decision:
Build Now.
Example 2: AI Avatar Fashion Prompt Skill
Repeated Task:
Not currently repeated inside MWMS.
Business Value:
Niche.
Decision:
Park unless AI Studio needs it later.
Example 3: Client Report Drafting Skill
Repeated Task:
Future AIBS likely.
Current Timing:
Future but high value.
Decision:
Park For Future AIBS Client Systems.
Example 4: Proof Review Skill
Repeated Task:
Likely across ads, sales, affiliate, client work.
Risk:
High.
Decision:
Build Soon or Build Now depending on current campaign needs.
Common Failure Modes
MWMS must prevent:
building skills from excitement
building too many skills
duplicating existing skills
creating vague skill names
creating skills without inputs
creating skills without outputs
creating skills without validation
creating skills before context exists
creating client skills too early
creating skills that should be frameworks
creating skills that should be checklists
forgetting parked skill ideas
letting the skill backlog become cluttered
Governance Role
HeadOffice owns the MWMS AI Skill Brainstorm And Prioritization Framework.
HeadOffice is responsible for:
approving skill prioritization logic
preventing skill sprawl
preventing duplicate skills
ensuring skills support real MWMS workflows
ensuring skill ideas are parked or rejected when appropriate
ensuring high-risk skills require review
ensuring future AIBS client skill ideas remain separated when needed
ensuring skill backlog remains useful
Individual Brains may propose skill ideas, but HeadOffice governs cross-Brain prioritization.
AI Business Systems Brain governs future client skill packaging.
AI Manager and AI Employee Router may later operationalize approved skills, but no technical action is authorized by this framework alone.
Relationship To Other MWMS Standards
This framework supports and must align with:
MWMS Document Structure Standard
MWMS AI Agent Skill Library Framework
MWMS AI Skill Builder And Audit Protocol
MWMS AI Skill Installation And Usage Protocol
MWMS Source Material To AI Skill Conversion Framework
MWMS AI Context Pack Template Standard
MWMS Offer Context Library Standard
MWMS AI Context Activation And Usage Protocol
MWMS AI Brain Readiness Review Checklist
MWMS AI Brain Audit And Decay Prevention Framework
MWMS Brain Routing Rule
MWMS MCR Promotion To Brain Protocol
MWMS Page Naming Standard
MWMS Architecture Registry
AI Business Systems Brain Canon
This framework defines how skill ideas are selected before they become formal MWMS skill records.
Drift Protection
This framework protects MWMS from:
skill sprawl
duplicate skills
vague skill ideas
premature skill creation
skills without context
skills without validation
skills without clear output
client skills created too early
frameworks being mistaken for skills
low-value skills increasing maintenance burden
Any skill idea that has not passed prioritization should not be treated as a formal skill.
Architectural Intent
The architectural intent of the MWMS AI Skill Brainstorm And Prioritization Framework is to keep MWMS skill creation disciplined.
MWMS will continue discovering many possible AI skills from courses, client work, internal workflows, and system failures.
The system needs a way to decide which ones matter.
The long-term goal is that every proposed skill can answer:
Does this task repeat?
Does MWMS have a specific method?
Would AI drift without guidance?
What input does it need?
What output does it create?
Which Brain owns it?
Which AI Employee uses it?
Can it be validated?
Does it duplicate an existing skill?
Is it needed now?
Should it be built, merged, parked, or rejected?
When MWMS can answer these questions consistently, skill creation becomes focused, useful, and scalable.
Change Log
v1.0 — Initial Draft
Created the MWMS AI Skill Brainstorm And Prioritization Framework as the framework for identifying, evaluating, ranking, parking, merging, rejecting, and prioritizing possible AI skills before formal skill creation.
This framework defines skill brainstorm sources, brainstorm questions, skill idea templates, prioritization tests, priority levels, scoring, backlog categories, build-now criteria, park criteria, reject criteria, merge and split criteria, brainstorm workflow, backlog review, examples, failure modes, governance role, drift protection, and architectural intent.
Change Impact Declaration
Pages Created:
MWMS AI Skill Brainstorm And Prioritization Framework
Pages Updated:
None
Pages Deprecated:
None
Registries Requiring Update:
MWMS Architecture Registry
HeadOffice Page Registry
AI Business Systems Brain Page Registry
AI Skill Registry
Canon Version Update Required:
No
Change Log Entry Required:
Yes
Employee Impact Check
Employees impacted:
HeadOffice Manager Employee
AI Manager
AI Employee Router
Skill Auditor
Course Absorption Agent
Context Library Builder
Content Planner Employee
Creative Strategist Employee
Offer Strategist Employee
Sales Strategist Employee
Research Analyst Employee
AI Business Systems Architect Employee
Required behaviour updates:
AI Employees must not recommend formal skill creation just because an idea sounds useful.
AI Employees must evaluate proposed skills against repetition, method clarity, drift risk, context dependency, output clarity, validation, business value, duplication risk, timing, and risk.
AI Employees must classify skill ideas as Build Now, Build Soon, Needs Method First, Needs Context First, Merge Candidate, Client-Specific Candidate, Automation Candidate Later, Parked, or Rejected.
AI Employees must prevent duplicate, vague, low-value, premature, or unvalidated skills from entering the active skill library.
END MWMS AI SKILL BRAINSTORM AND PRIORITIZATION FRAMEWORK v1.0