System: MWMS
Document Type: Framework
Authority Level: MCR Source Of Truth
Status: Draft For MCR
Version: v1.1
Primary Location: MCR
Future Operational Destination: HeadOffice Brain, AIBS Brain, AI Manager, AI Employee Router, Content Brain, Offer Brain, Sales Brain, Research Brain, Course Absorption System, Future AIBS Client Systems
Parent Page: HeadOffice
Owner: Martyn
Developer Boundary: No Development Action Authorized By This Page
Source Of Truth: MCR
Last Reviewed: 2026-06-20
Source / Origin: MWMS Source Material To AI Skill Conversion Framework v1.0 + AI Automations by Jack — reusable Skills, expert-workflow conversion, project-scoped capabilities, skill packaging, specialist tool integration, Claude Code persistent instruction patterns and multi-output workflow examples
Related Pages: MWMS AI Agent Skill Library Framework, MWMS AI Skill Builder And Audit Protocol, MWMS Manual Build Versus Skill Build Decision Rule, MWMS AI Employee Capability Stack Framework, MWMS AI Tool Permission And Access Framework, MWMS AI Agent Memory And Context Framework, MWMS Tool-Agnostic Context Portability Protocol, MWMS AI Output Validation Standard
Purpose
The purpose of this document is to define the MWMS Source Material To AI Skill Conversion Framework.
This framework establishes how MWMS converts existing source material into reusable AI skills, AI Employee procedures, client-facing AI workflows, internal operating playbooks, or structured context-driven assistants.
MWMS must not treat valuable source material as passive reference content.
Books, courses, manuals, frameworks, SOPs, transcripts, newsletters, sales assets, workshop notes, and internal documents may contain repeatable procedures that can become AI skills.
This framework exists to help MWMS identify when source material contains:
repeatable process
decision logic
workflow steps
diagnostic rules
content structures
sales logic
research procedures
quality checks
client delivery methods
AI Employee training value
future AIBS client skill potential
The goal is to transform useful source material into operational skill intelligence.
Without this framework, MWMS risks:
leaving useful procedures trapped inside documents
turning source material into summaries instead of skills
creating AI Employees without procedural depth
duplicating skills across Brains
using source material without quality checks
mistaking information for skill
building skills from weak content
missing future AIBS client productization opportunities
The Source Material To AI Skill Conversion Framework turns strong source material into reusable AI working capability.
Scope
This framework applies to all MWMS work where existing source material may contain procedures that can become AI skills or AI Employee workflows.
This includes:
books
course transcripts
course PDFs
manuals
SOPs
framework documents
client documents
internal MWMS pages
sales scripts
workshop notes
training material
newsletter systems
research workflows
content systems
ad creation systems
offer evaluation systems
developer handoff systems
client delivery processes
This framework supports:
HeadOffice Brain
AIBS Brain
AI Manager
AI Employee Router
Course Absorption System
Content Brain
Offer Brain
Sales Brain
Creative Brain
Research Brain
Affiliate Brain
Ads Brain
Operations Brain
Future AIBS Client Systems
This framework does not authorize technical development, plugin changes, Supabase changes, WordPress changes, automation wiring, client implementation, or M developer action.
Core Definition
Source Material To AI Skill Conversion is the process of identifying repeatable procedural intelligence inside a source document and converting it into a structured AI skill.
A source document may teach what is true.
An AI skill teaches how to do the work.
Not all useful source material should become a skill.
Some material should become:
context file
framework page
reference page
checklist
audit rule
prompt pattern
asset template
parking item
ignore item
A skill should be created only when the source material contains repeatable work that an AI Employee can perform or assist with.
Core Principle
The core principle of this framework is:
Information becomes valuable to MWMS when it can improve decision-making, execution, validation, or repeatable work.
A good AI skill is not copied from source material.
It is extracted, structured, governed, validated, and adapted to MWMS.
The source provides the raw method.
MWMS converts that method into an operational skill.
Skill Conversion Test
Before converting source material into an AI skill, MWMS must apply the Skill Conversion Test.
Question 1: Does The Source Contain A Repeatable Procedure?
The source should include a process that can be followed again.
Examples:
how to audit content
how to build a lead magnet
how to assess offer fit
how to prepare a webinar
how to extract customer language
how to review ad angles
If the source is mostly opinion or inspiration, it may not become a skill.
Question 2: Does The Procedure Support A Real MWMS Workflow?
The skill should help MWMS do work that matters.
Examples:
course absorption
offer evaluation
client onboarding
content planning
sales asset drafting
creative review
research synthesis
context library creation
If the procedure does not support a useful workflow, park it.
Question 3: Can The Input Be Defined?
The AI Employee must know what input the skill requires.
Examples:
source document
client intake form
offer profile
customer reviews
sales page
transcript
newsletter
ad library
If input cannot be defined, the skill is not ready.
Question 4: Can The Output Be Defined?
The skill must produce a clear output.
Examples:
audit report
context file
content brief
lead magnet outline
objection map
skill record
handoff package
If output is vague, do not formalize the skill yet.
Question 5: Can The Skill Be Validated?
MWMS must be able to check whether the skill worked.
If the output cannot be validated, the skill should remain draft or reference material.
Question 6: Does This Improve MWMS More Than Existing Skills?
If MWMS already has a stronger skill or standard, the new material may merge into the existing skill instead of creating a new one.
Possible Outcomes
Create New Skill
Merge Into Existing Skill
Update Existing Skill
Create Framework Instead
Create Checklist Instead
Park For Later
Ignore
No conversion should end in ambiguity.
Source Material Categories
MWMS recognizes several source material categories.
Procedural Source Material
Contains clear steps or process.
Best outcome:
AI skill, SOP, workflow, checklist.
Strategic Source Material
Contains strategic thinking, positioning, judgment, or decision logic.
Best outcome:
framework, expert thinking rules, decision skill.
Contextual Source Material
Contains facts, voice, buyer language, proof, or offer details.
Best outcome:
context library update.
Creative Source Material
Contains hooks, stories, patterns, angles, examples, or templates.
Best outcome:
creative pattern library, content skill, ad skill.
Reference Source Material
Contains useful but non-procedural information.
Best outcome:
reference page, source note, parking item.
Weak Source Material
Contains generic, duplicated, outdated, or shallow advice.
Best outcome:
ignore or archive.
Skill Extraction Workflow
MWMS uses the following workflow to convert source material into a skill.
Step 1: Identify The Source
Define what material is being reviewed.
Examples:
book chapter
course lesson
transcript
manual
client process document
MWMS framework page
Step 2: Identify The Core Procedure
Find the repeatable work inside the source.
Ask:
What is the source teaching someone to do?
What sequence is implied?
What decision rules are included?
What output is expected?
Step 3: Separate Knowledge From Procedure
Separate what the source knows from what the skill does.
Knowledge may become context.
Procedure may become skill.
Step 4: Map To MWMS Workflow
Identify where this skill would be used inside MWMS.
Examples:
Course Absorption
Offer Evaluation
Content Planning
Client Intake
Sales Support
Research Synthesis
Creative Review
Step 5: Identify Owning Brain
Assign the skill to the correct Brain.
Examples:
Content Brain
Offer Brain
Sales Brain
Research Brain
HeadOffice Brain
AIBS Brain
Step 6: Define Required Input
List the input the AI Employee needs.
Step 7: Define Required Context
List the context files or standards the skill must read.
Step 8: Define Procedure
Convert the source method into clear MWMS procedure.
Step 9: Define Forbidden Actions
State what the skill must not do.
Step 10: Define Output
Define the result the skill must produce.
Step 11: Define Validation
Define how MWMS checks the output.
Step 12: Assign Status
Most converted skills should begin as Draft or Manual Use.
Step 13: Test Against Real Material
Run the skill on realistic inputs before using it operationally.
Step 14: Test Failure Conditions
Test missing input, unclear context, wrong scope, unavailable tools, weak sources and invalid outputs.
Step 15: Verify Scope
Confirm whether the candidate is organisation-level, Brain-level, workflow-level, project-level, client-level or experimental.
Step 16: Verify Dependencies
Confirm required tools, supporting skills, files, permissions and environment assumptions.
Step 17: Measure Outcome
Confirm whether the converted skill improves quality, speed, consistency, risk control or business value.
Step 18: Assign Conversion Decision
Choose one clear outcome:
Create New Skill
Update Existing Skill
Extend Existing Skill
Compose Existing Skills
Create Framework
Create Checklist
Create Context Update
Create Template
Use Temporary Procedure
Park
Reject
Source Decomposition Model
Before converting source material, MWMS should separate the source into distinct intelligence types.
Possible components include:
Principles
What the source believes is true.
Procedures
What the source teaches someone to do.
Decision Rules
How the source determines what to do next.
Inputs
What the procedure requires.
Outputs
What the procedure produces.
Examples
Illustrations of how the method works.
Templates
Reusable structures that support the method.
Tools
Software or systems used to execute the procedure.
Claims
Statements that require validation.
Context
Facts, terminology, voice, buyer language, proof or operating assumptions.
Risks
Failure conditions, limitations or cautions.
Decomposition Rule
Do not convert a whole source into one skill by default.
Extract only the procedural elements that support a real MWMS workflow.
Different parts of the same source may become:
a framework
a skill
a checklist
a context update
a template
a reference record
a parking item
an ignored item
Expert Workflow Capture
A source may describe an expert workflow incompletely.
The conversion process should identify:
the visible steps
the hidden judgement points
the order of operations
required experience
quality thresholds
stop conditions
exception handling
what the expert checks before moving forward
what the expert rejects
what the expert does when evidence is weak
Where the source omits critical judgement, MWMS should not pretend the procedure is complete.
Possible outcomes:
Request More Source Material
Keep As Draft Skill
Create Framework Only
Add Human Review Gate
Reject Conversion
Expert Workflow Rule
A source is not skill-ready merely because it lists steps.
The steps must contain enough decision logic, boundaries and validation to support reliable execution.
Source Authority And Provenance
Each conversion should preserve source provenance.
Record:
source title
source creator
source type
source date
date accessed
lesson, chapter or section
files used
supporting examples
known limitations
whether the source is primary, secondary or promotional
whether MWMS has tested the method
Source Authority Levels
Level A — Internal Proven Procedure
A method already proven inside MWMS.
Level B — Strong External Procedure
A detailed and credible external operating method.
Level C — Useful External Pattern
A reusable pattern requiring significant MWMS adaptation.
Level D — Promotional Or Weak Material
Claims or summaries without enough procedure to justify conversion.
Authority Rule
Level D material should not become a formal skill without stronger evidence and substantial reconstruction.
Tool-Specific To Tool-Agnostic Conversion
External sources often tie procedures to one product, interface, model or platform.
MWMS should separate:
Durable Procedure
The underlying method.
Implementation Route
The current tool-specific execution method.
Tool-Specific Instructions
Commands, settings or interface steps that may change.
The conversion should preserve:
purpose
inputs
decision logic
sequence
validation
outputs
failure handling
The conversion should isolate:
vendor commands
temporary model names
interface paths
pricing
quota limits
tool-specific installation steps
Tool-Agnostic Rule
The durable skill should survive a change in tools where practical.
Tool-specific notes may be stored as replaceable implementation guidance.
Source-To-Skill Capability Gap Check
A skill should only be created or updated when the source closes a real capability gap.
Ask:
Which AI Employee lacks this capability?
Which workflow requires it?
What repeated problem does it solve?
Why is the existing Skill Library insufficient?
Would an update to an existing skill be enough?
Can the new capability be tested?
Can its value be measured?
Capability Gap Outcomes
Update Existing Skill
Extend Existing Skill
Compose Existing Skills
Create New Skill
Create Temporary Procedure
Create Reference Only
Park
Reject
Capability Gap Rule
No real capability gap, no new skill.
Skill Candidate Scope
Every converted skill candidate should receive a proposed scope.
Possible scopes:
Organisation-Level
Brain-Level
Workflow-Level
Project-Level
Client-Level
Experimental
Scope should be determined by:
source relevance
data sensitivity
workflow ownership
tool dependencies
client boundaries
procedure stability
risk
proof of value
Scope Rule
Begin with the narrowest practical scope.
Do not promote a client, project or experimental procedure into general MWMS use without review and proof.
Source Asset Bundle
Some sources include multiple supporting assets.
Possible assets include:
main document
templates
checklists
examples
prompts
scripts
code
configuration files
visual references
test data
output samples
supporting videos
An asset bundle should be reviewed to determine which files become:
skill procedure
input schema
output template
validation checklist
example set
test case
implementation note
reference only
excluded material
Asset Bundle Rule
Supporting assets do not automatically inherit authority from the main source.
Each asset must be inspected for relevance, safety, duplication and operational value.
Multi-Output Conversion
Some source procedures produce several related outputs.
Examples:
one research process may produce a competitor report, executive brief and meeting questions
one content process may produce an article, newsletter, social posts and video brief
one lead-magnet process may produce the asset, landing-page outline and follow-up sequence
A multi-output skill may be justified when:
all outputs share one verified source
the outputs support one business purpose
the workflow remains coherent
validation remains manageable
output volume creates real value
Multi-Output Rule
Do not convert a source into a multi-output skill merely because the tool can generate many formats.
Each output must have a defined destination and purpose.
Conversion Output Template
Use the following structure when converting source material into a skill.
Source Material:
Source Type:
Source Value:
Source Authority Level:
Source Provenance:
Capability Gap Addressed:
Candidate Skill Name:
Owning Brain:
Assigned AI Employee:
Proposed Skill Scope:
Workflow Supported:
Skill Purpose:
When To Use:
Required Input:
Required Context:
Required Tools Or Dependencies:
Procedure Extracted:
MWMS Adaptation Required:
Tool-Specific Elements To Isolate:
Forbidden Actions:
Required Output:
Validation Requirement:
Test Cases Required:
Human Review Requirement:
Handoff Destination:
Skill Status:
Expected Outcome:
Outcome Evidence:
Recommended Action:
Notes:
Skill Adaptation Rules
Rule 1: Do Not Copy The Source Blindly
The source method must be translated into MWMS language, standards, Brains, and workflow logic.
Rule 2: Do Not Create Duplicate Skills
Check whether an existing skill or standard already covers the procedure.
Rule 3: Preserve Useful Procedure
Do not discard useful step logic just because the source uses different language.
Rule 4: Remove Hype
Source material may contain marketing language.
MWMS skills must use operational language.
Rule 5: Add Governance
Most source procedures will not include MWMS governance.
Add:
human review
source grounding
forbidden actions
risk boundaries
handoff destination
validation
Rule 6: Add Brain Ownership
A skill must belong to a Brain.
Rule 7: Add Context Requirements
A skill must know what context it needs.
Rule 8: Add Failure Triggers
A skill must know when to stop, park, or escalate.
Rule 9: Assign Conservative Status
New converted skills should not be treated as proven.
Start as Draft or Manual Use.
Rule 10: Test Before Operational Use
No converted skill should be automated or client-facing until tested.
Rule 11: Preserve Provenance
Record where the procedure came from and what MWMS changed.
Rule 12: Separate Durable Procedure From Tool Instructions
Tool-specific commands should remain replaceable.
Rule 13: Start With Narrow Scope
Converted skills should begin in the smallest safe environment.
Rule 14: Test Negative Cases
The skill must fail safely when source, context, permission or dependency is missing.
Rule 15: Measure Operational Value
A converted skill must create more than an impressive output.
It should improve a real workflow.
Framework Versus Skill Decision
Not all source material should become a skill.
Create a Framework when the source defines a concept, model, or way of thinking.
Create a Skill when the source defines repeatable execution.
Create a Checklist when the source defines review criteria.
Create a Context File when the source contains facts, voice, buyer, proof, or offer details.
Create a Reference when the source is useful but not active procedure.
Park when the source may be useful later but has no current workflow.
Ignore when the source is weak, duplicated, generic, or irrelevant.
Examples
Example 1: Course Lesson On Customer Interviews
Possible outcome:
Research Brain Customer Interview Extraction Skill
or
Research Brain Customer Interview Framework
Decision depends on whether the material teaches a repeatable interview process or a general concept.
Example 2: Book Chapter On Brand Voice
Possible outcome:
Voice Architecture Context File Update
or
Voice Checker Skill
If it defines voice principles, update context.
If it defines how to review copy against voice, create skill.
Example 3: Workshop On Lead Magnets
Possible outcome:
Context-Grounded Lead Magnet Builder Skill
or
Lead Magnet Funnel Framework update.
If it teaches the asset strategy, update framework.
If it provides repeatable build steps, create skill.
Example 4: Sales Script Framework
Possible outcome:
Sales Brain Objection Handling Skill
Sales Brain Discovery Call Skill
Sales Brain Follow-Up Message Skill
depending on repeatability and output.
Source Quality Checks
Before converting source material, check:
Is the source specific?
Is it operational?
Is it current?
Is it superior to what MWMS already has?
Does it improve a real workflow?
Does it contain reusable steps?
Does it include decision logic?
Does it include examples?
Does it avoid unsupported claims?
Can it be governed?
Can it be validated?
If the source fails these checks, do not convert it into a formal skill.
Course Absorption Application
This framework is especially useful for course absorption.
When course material contains procedural value, the Course Absorption Agent should decide whether the material should become:
new skill
skill update
framework page
context library update
checklist
parking item
ignore item
Course material should not become a skill just because the instructor labels it a skill, template, framework, or system.
MWMS must decide based on actual procedural value.
Client System Application
Future AIBS clients may have source material that can become client-specific skills.
Examples:
client sales call process
client onboarding procedure
client support response style
client content planning method
client reporting process
client proposal method
client coaching method
Client skill conversion must remain isolated.
Client-specific skills must not be reused across clients unless deliberately generalized and approved.
Source-To-Skill Risk Areas
MWMS must watch for risks.
Risk 1: Weak Source Becomes Formal Skill
This creates documentation clutter.
Risk 2: Duplicate Skill Creation
This creates conflicting procedures.
Risk 3: Tool-Specific Procedure
The source may depend on one AI platform.
Translate into tool-agnostic logic where possible.
Risk 4: Missing Validation
Many external procedures do not include validation.
MWMS must add validation.
Risk 5: Missing Human Review
External workflows may imply automation too early.
MWMS must add review gates.
Risk 6: Client Context Leakage
Client source material must not become general MWMS skill without approval.
Risk 7: Hype-Based Procedure
Marketing claims must be removed.
MWMS needs operational procedure.
Validation Checklist
Before approving a converted skill, check:
Does the task repeat?
Is the procedure clear?
Is the owning Brain clear?
Is the assigned AI Employee clear?
Is required input defined?
Is required context defined?
Is the output defined?
Are forbidden actions defined?
Is validation defined?
Is human review defined?
Is handoff destination defined?
Is the source superior or useful?
Does this duplicate an existing skill?
Does it close a real capability gap?
Is source provenance preserved?
Is the source authority sufficient?
Is the tool-specific layer separated from the durable procedure?
Is the proposed scope appropriate?
Are dependencies defined?
Have negative tests been defined?
Can the outcome be measured?
Should this be a framework instead?
Should this be parked?
Common Failure Modes
MWMS must prevent:
turning every source into a skill
copying source language without MWMS translation
creating duplicate skills
creating vague skills
creating skills without Brain ownership
creating skills without validation
creating skills without input requirements
creating skills without output requirements
treating summaries as skills
treating templates as skills
treating tools as skills
creating client-specific skills inside general MWMS context
promoting untested skills too early
losing source provenance
copying vendor-specific commands into permanent procedure
creating a skill without a capability gap
using client or project procedures as global skills
failing to inspect supporting assets
creating multi-output skills with no destination or purpose
measuring output volume instead of operational value
Governance Role
HeadOffice owns the MWMS Source Material To AI Skill Conversion Framework.
HeadOffice is responsible for:
deciding whether source material should become a skill
preventing duplicate skill creation
ensuring source material is translated into MWMS structure
ensuring skill candidates have Brain ownership
ensuring validation and human review rules are included
ensuring weak material is parked or ignored
ensuring client source material remains isolated
ensuring converted skills remain aligned with the AI Agent Skill Library Framework
ensuring source provenance is preserved
ensuring capability gaps are genuine
ensuring tool-specific instructions are isolated
ensuring converted skills receive the correct scope
ensuring supporting assets are inspected
ensuring test cases include failure conditions
ensuring operational value is measured
Individual Brains may propose skills from source material, but HeadOffice governs cross-Brain, MCR, high-risk, and client-facing skill conversion.
Relationship To Other MWMS Standards
This framework supports and must align with:
MWMS Document Structure Standard
MWMS Course Absorption Operating Rule
MWMS AI Agent Skill Library Framework
MWMS AI Skill Builder And Audit Protocol
MWMS AI Agent Memory And Context Framework
MWMS Client IP Excavation Framework
MWMS Offer Context Library Standard
MWMS Context Library Governance And Folder Map Standard
MWMS AI Context Activation And Usage Protocol
MWMS AI Brain Audit And Decay Prevention Framework
MWMS Tool-Agnostic Context Portability Protocol
MWMS Context-Driven Asset Builder Framework
MWMS Content Intelligence Scanner Framework
MWMS AI Output Validation Standard
MWMS Messy Input Normalization Framework
MWMS Brain Routing Rule
MWMS MCR Promotion To Brain Protocol
MWMS Page Naming Standard
MWMS Architecture Registry
AIBS Brain Canon
This framework defines how existing source material becomes reusable procedural capability.
Drift Protection
This framework protects MWMS from:
passive source material
summaries mistaken for skills
weak source material becoming formal process
duplicate skill creation
tool-specific lock-in
client context leakage
skills without validation
skills without output definitions
skills without Brain ownership
course hype being mistaken for operational value
manual procedures being lost inside documents
Any source-to-skill conversion that does not define procedure, input, output, validation, owner, and forbidden actions should be treated as a drift risk.
Architectural Intent
The architectural intent of the MWMS Source Material To AI Skill Conversion Framework is to turn useful existing knowledge into reusable AI working capability.
MWMS will absorb many courses, books, documents, and client materials.
Not all of that material should become canon.
Not all of it should become a skill.
But when source material contains a repeatable way to do valuable work, MWMS should be able to convert that method into a governed AI skill.
The long-term goal is that every source-to-skill decision can answer:
What source material is being used?
What authority and provenance does the source have?
What capability gap does it close?
What procedure does it contain?
Which Brain owns the procedure?
Which AI Employee should use it?
What input does it require?
What context does it need?
What output does it produce?
What scope should the converted skill have?
Which tool-specific elements must remain replaceable?
What dependencies and test cases are required?
How is it validated?
What must it not do?
Should this become a new skill, update or extend an old skill, compose existing skills, become a framework, checklist, context update, template, temporary procedure, parking item, or rejection?
What evidence will prove that the conversion created operational value?
When MWMS can answer these questions consistently, external knowledge and internal experience become reusable AI capability instead of passive information.
Change Log
Version: v1.1
Date: 2026-06-20
Author: HeadOffice
Change:
Updated the MWMS Source Material To AI Skill Conversion Framework using the AI Automations by Jack block covering reusable Skills, expert-workflow conversion, specialist capabilities, project-scoped procedures, tool-specific implementation notes, supporting asset bundles, multi-output workflows and persistent instruction systems.
Added:
Source Decomposition Model
Expert Workflow Capture
Source Authority And Provenance
Tool-Specific To Tool-Agnostic Conversion
Source-To-Skill Capability Gap Check
Skill Candidate Scope
Source Asset Bundle
Multi-Output Conversion
expanded Conversion Output Template
failure-condition testing
scope verification
dependency verification
outcome measurement
expanded conversion decisions
new adaptation rules
expanded validation checklist
expanded common failure modes
Purpose of update:
To evolve the framework from a basic source-extraction process into a complete provenance-aware, capability-gap-driven and tool-agnostic conversion system that can turn proven external or internal methods into properly scoped, tested and outcome-linked MWMS skills.
v1.0 — Initial Draft
Created the MWMS Source Material To AI Skill Conversion Framework as the framework for converting books, courses, manuals, transcripts, SOPs, client documents, internal MWMS pages, and other source material into reusable AI skills, AI Employee procedures, checklists, frameworks, or context library updates.
This framework defines the skill conversion test, source material categories, extraction workflow, conversion template, adaptation rules, framework-versus-skill decisions, examples, quality checks, course absorption application, client system application, risk areas, validation checklist, common failure modes, governance role, drift protection, and architectural intent.
Change Impact Declaration
Pages Created:
None
Pages Updated:
MWMS Source Material To AI Skill Conversion Framework
Pages Deprecated:
None
Standalone Pages Not Created:
MWMS Source Decomposition Standard
MWMS Expert Workflow Capture Framework
MWMS Source Provenance For Skills Standard
MWMS Tool-Specific To Tool-Agnostic Skill Conversion Standard
MWMS Skill Candidate Scope Framework
MWMS Source Asset Bundle Standard
MWMS Multi-Output Skill Conversion Framework
Registries Requiring Update:
None confirmed by the supplied source.
Canon Version Update Required:
No
Change Log Entry Required:
Yes
Strategic Absorption Result
MWMS gains a stronger source-conversion system that separates principles, procedures, context, tools and claims; preserves provenance; identifies genuine capability gaps; converts expert workflows into appropriately scoped and testable skills; isolates temporary vendor instructions; and measures whether the resulting capability improves a real MWMS or AIBS workflow.
Employee Impact Check
Employees impacted:
HeadOffice Manager Employee
Course Absorption Agent
AI Manager
AI Employee Router
Skill Auditor
Context Library Builder
Research Analyst Employee
Content Planner Employee
Offer Strategist Employee
Sales Strategist Employee
AIBS Architect Employee
Required behaviour updates:
AI Employees must evaluate whether source material contains repeatable procedural value before recommending skill creation.
AI Employees must not convert every useful document into a skill.
AI Employees must decide whether source material should become a new skill, update an existing skill, become a framework, become a checklist, update a context library, be parked, or be ignored.
AI Employees must translate source material into MWMS structure rather than copying external language directly.
AI Employees must include Brain ownership, required input, required context, procedure, forbidden actions, output, validation, handoff, status, and review requirements for converted skills.
AI Employees must preserve source provenance and authority level.
AI Employees must confirm a real capability gap before creating a new skill.
AI Employees must separate durable procedure from temporary tool-specific instructions.
AI Employees must assign the narrowest appropriate skill scope.
AI Employees must inspect supporting asset bundles and define both positive and negative test cases.
AI Employees must measure whether the converted skill creates operational value.
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