MWMS Source Visibility And Evidence Display Standard

System: MWMS
Document Type: Standard
Status: Draft For MCR
Authority: HeadOffice
Applies To: Research Brain, Affiliate Brain, Ads Brain, Content Brain, HeadOffice Intelligence, Data Brain, Experimentation Brain, Risk Brain, AI Employees, Deep Search Workflows, Future Client Facing AI Systems
Primary Location: MCR
Future Operational Destination: mwmsbrain.site, mwmsheadofficebrain.site, Brain Room, Research Brain, Affiliate Brain, Ads Brain, AI Employee Dashboards, HeadOffice Dashboards, Future Client Portals
Parent Page: HeadOffice
Source Of Truth: MCR
Related Frameworks: MWMS Deep Search Quality And Observability Framework, MWMS Research Planning And Query Rewriting Standard, MWMS AI Guardrail And Preflight Check Standard, MWMS AI Work Session Persistence Standard, MWMS AI Observability Metadata Standard, MWMS AI Employee Evaluation Scorecard Standard, MWMS Agent Loop Control Framework
Course Source: Matt Pocock AIhero Build DeepSearch In TypeScript
Absorption Status: Approved For Integration

Purpose

The purpose of this standard is to define how MWMS displays sources, evidence, and source confidence to human operators.

MWMS AI Employees must not only produce answers.

They must show what evidence was used, where it came from, how reliable it appears, how fresh it is, and whether it supports the final decision.

This standard ensures source evidence is not hidden inside backend traces, raw logs, or model reasoning.

The operator should be able to see:

which sources were used
which sources were inspected
which sources were ignored
what each source contributed
whether sources were current
whether sources were reliable
whether sources conflicted
whether the final answer was properly supported

The goal is to make AI-generated intelligence easier to trust, review, audit, and improve.

Scope

This standard applies to any MWMS workflow where sources, evidence, research, or external information influence an output or decision.

This includes:

Deep Search workflows
Research Brain investigations
Affiliate Brain offer evaluations
Ads Brain compliance reviews
Content Brain research workflows
HeadOffice Intelligence reviews
Newsletter Intelligence follow-up research
Product or vendor research
Tool evaluations
Source inspections
Market trend research
Compliance and policy checks
Experimentation Brain analysis
Risk Brain reviews
Future client-facing AIBS research outputs

This standard does not define exact frontend code, React components, scraping implementation, or source database table structure.

It defines the MWMS governance standard for showing evidence to operators.

Core Rule

The core rule is:

Sources used by AI Employees should be visible to the operator, not hidden only in backend trace logs.

If an AI Employee uses sources to support an answer, the operator should be able to inspect the evidence behind that answer.

A source-backed answer without visible source evidence is incomplete.

Definition Of Source Visibility

Source visibility means the human operator can see the source evidence behind an AI output.

Source visibility should answer:

What sources did the AI use?
What sources were inspected?
What did each source say?
Was the source official, expert, commercial, user-generated, or unknown?
Was the source current enough?
Was the source trusted?
Was the source actually used in the final answer?
Did any source conflict with another?
Did the AI answer rely on strong or weak evidence?

Source visibility turns AI output from a black-box answer into a reviewable intelligence record.

Definition Of Evidence Display

Evidence display is the user-facing presentation of the source material, evidence summaries, trust indicators, freshness indicators, and support status behind an AI answer.

Evidence display may appear as:

source cards
evidence panels
expandable source lists
citation rows
source summaries
trust and freshness badges
source conflict warnings
evidence sufficiency notes
final answer support map
HeadOffice review panels

Evidence display is not the same as raw logs.

It should be readable, structured, and useful to the operator.

Why MWMS Needs This Standard

Without source visibility, MWMS risks:

trusting polished but unsupported answers
missing outdated sources
missing weak evidence
hiding source conflicts
making poor affiliate decisions
making risky ad compliance decisions
approving weak content
repeating research
losing auditability
weakening HeadOffice oversight
making AI Employees harder to evaluate
making future client-facing systems less trustworthy

With source visibility, MWMS gains:

operator trust
better review quality
stronger evidence discipline
better compliance safety
better Research Brain outputs
better Affiliate Brain offer decisions
better Ads Brain policy review
better HeadOffice intelligence
reusable source records
clearer Kaizen learning

Source Visibility Versus Observability

Observability is for tracing what the system did.

Source visibility is for showing the operator what evidence supports the answer.

Observability	Source Visibility
backend trace	operator-facing evidence view
model actions	source evidence
tool activity	source cards
database actions	source summaries
cost and latency	trust/freshness indicators
debugging	review and decision support

Both are needed.

A backend trace may show that a source was inspected.

Source visibility shows whether that source was useful, current, trusted, and relevant.

Source Visibility Versus Citations

Citations show where information came from.

Source visibility shows whether the source is useful and trustworthy.

A citation alone is not enough.

MWMS should aim to show:

source title
source URL
source type
source date
retrieved date
trust rating
freshness rating
evidence summary
relevance to task
used in final answer yes/no
limitations or conflicts

A link without source context is weak evidence display.

Required Source Display Fields

Each displayed source should include, where available:

Field	Description
source_title	Human-readable title
source_url	Source link or source record reference
source_type	Official, expert, commercial, user-generated, unknown
source_owner	Vendor, platform, publication, user, organisation
publication_date	Date published if visible
last_updated_date	Date updated if visible
retrieved_at	Date/time MWMS retrieved it
freshness_rating	Current, acceptable, possibly outdated, outdated, unknown
trust_rating	High, medium, low, unknown
relevance_rating	High, medium, low
evidence_summary	What useful evidence the source provided
key_claims	Main claims or facts extracted
limitations	What the source does not prove
used_in_final_output	Yes or no
conflict_detected	Yes or no
source_status	Inspected, not inspected, failed, blocked, ignored

Recommended Source Card Format

A source card should be readable at a glance.

Recommended format:

Source Title:
[Title]

Source Type:
Official / Expert / Commercial / User-Generated / Unknown

Freshness:
Current / Acceptable / Possibly Outdated / Outdated / Unknown

Trust:
High / Medium / Low / Unknown

Evidence Summary:
[Short summary of what this source contributed]

Used In Final Answer:
Yes / No

Limitations:
[What this source does not prove or where caution is needed]

This can later become a UI component on mwmsbrain.site or mwmsheadofficebrain.site.

Source Type Classification

MWMS should classify source types.

Official Source

Examples:

vendor documentation
official product page
platform policy page
government page
company announcement
official changelog
affiliate network page

Default trust level: high, but still checked for bias and freshness.

Expert Source

Examples:

respected industry publication
specialist blog
analyst report
credible technical article
recognised practitioner source

Default trust level: medium to high.

Commercial Source

Examples:

sales page
affiliate review page
comparison page with commissions
agency landing page
vendor marketing page

Default trust level: medium to low unless corroborated.

User-Generated Source

Examples:

Reddit
forums
comments
social media posts
community discussion

Default trust level: signal only, not proof.

Unknown Source

Examples:

content farms
anonymous blogs
scraped reposts
pages with unclear ownership
thin AI-generated content

Default trust level: low.

Freshness Display Standard

Every source used in time-sensitive workflows should show freshness.

Freshness ratings:

Rating	Meaning
Current	Suitable for current decision-making
Acceptable	Recent enough for the task
Possibly Outdated	Use with caution
Outdated	Should not be trusted for current decisions
Unknown	No clear date or freshness signal
Not Applicable	Evergreen or historical source

Freshness matters most for:

pricing
affiliate payouts
product availability
platform policies
laws and regulations
AI tool features
software documentation
advertising rules
market trends
current events
compliance matters

Rule

If freshness matters and the source date is unknown, the source should not be displayed as high confidence.

Trust Display Standard

Sources should display a trust rating where possible.

Trust ratings:

Rating	Meaning
High	Official, credible, directly relevant, low bias
Medium	Useful but may require corroboration
Low	Weak, biased, indirect, outdated, or questionable
Unknown	Not enough information to judge

Trust rating should consider:

source owner
source type
publication quality
bias
commercial incentive
directness of evidence
freshness
corroboration
history of reliability

Rule

A low-trust source may be shown as a signal, but should not be treated as proof.

Relevance Display Standard

A source should show how relevant it is to the task.

Relevance ratings:

Rating	Meaning
High	Directly answers or supports the task
Medium	Supports part of the task
Low	Background only or weakly related

A source can be trustworthy but not relevant.

A source can be relevant but not trustworthy.

Both must be visible.

Evidence Summary Rule

Each source should include a short evidence summary.

The summary should answer:

What did this source contribute?
What claim or fact did it support?
Why was it useful?
What limitation should the operator know?

The summary must not invent missing evidence.

If the source does not answer the needed question, the summary should say so.

Used In Final Output Rule

MWMS should show whether a source was actually used in the final answer.

Possible statuses:

Status	Meaning
Used	Source supported final answer
Not Used	Source inspected but not used
Background Only	Helped context but not final claim
Rejected	Source was weak, irrelevant, or unreliable
Failed	Source could not be inspected
Conflicting	Source conflicted with other evidence

This helps operators understand the evidence path.

Source Conflict Display Rule

If sources conflict, the operator should see it.

Conflict display should include:

conflicting sources
what they disagree on
which source appears stronger
whether the conflict affects confidence
whether human review is required

Rule

Source conflict should lower confidence unless resolved.

The AI Employee should not hide disagreement between sources.

Evidence Sufficiency Display

The final output should include an evidence sufficiency rating where relevant.

Suggested ratings:

Rating	Meaning
Strong	Evidence is reliable, current, and directly supports answer
Acceptable	Evidence supports answer but has minor limitations
Weak	Evidence is incomplete, indirect, old, or uncertain
Insufficient	Not enough evidence to support a trusted answer

Evidence sufficiency should influence:

confidence score
human review requirement
final recommendation
whether the workflow continues
whether the result is parked or escalated

Source Display By Workflow Type

Different workflows require different source display depth.

Deep Search

Should show:

all inspected sources
evidence summaries
trust/freshness ratings
used-in-answer status
conflicts
evidence sufficiency

Affiliate Offer Evaluation

Should show:

vendor/product source
affiliate network source
customer complaint/review signals
competitor sources
compliance/policy sources where relevant
payout or terms source if available

Ads Compliance Review

Should show:

official policy source
product claim source
compliance risk evidence
jurisdiction source if relevant
source freshness

Content Research

Should show:

topic sources
competing content
authority sources
freshness rating
search intent evidence

HeadOffice Intelligence

Should show:

original newsletter/source
supporting external sources if researched
business relevance evidence
routing basis
risk/confidence notes

Client-Facing Output

Should show sources carefully, with privacy and simplicity controls.

Client-facing source display may be simplified, but internal evidence must remain available.

Operator UI Source Panel

Future MWMS interfaces should include an operator source panel where useful.

A source panel may include:

source list
source cards
filters by type/trust/freshness
used versus unused sources
conflicts
evidence summary
source inspection status
open source link
copy source summary
create source record
route source issue to Research Brain
mark source as weak
add human review note

This is especially valuable for HeadOffice, Research Brain, Affiliate Brain, and Ads Brain.

Source Visibility Levels

Not all users need the same source visibility.

Suggested visibility levels:

Level	Meaning
Internal Full Evidence	Full source detail for MWMS operators
HeadOffice Review	Evidence plus risk/confidence indicators
Developer Debug	Source plus retrieval/tool metadata
Client Summary	Simplified sources and explanation
Hidden/Internal Only	Sensitive sources not shown to client
Archived Evidence	Historical source record kept for audit

Rule

Internal MWMS evidence should be richer than client-facing evidence.

Source Privacy And Safety Rule

Source display must not expose sensitive information unnecessarily.

Do not expose:

private credentials
private user data
restricted client data
internal API responses
private financial details
confidential source excerpts
copyrighted long-form content beyond what is allowed
private email content unless authorised

Where needed, display:

source reference
short summary
redacted excerpt
internal-only tag
access-restricted link

Evidence Display In AI Work Sessions

Source visibility should connect to MWMS AI Work Session Persistence Standard.

A persistent AI work session should store:

source IDs
source summaries
source ratings
evidence sufficiency
sources used in final answer
conflicts detected
review notes
source-related Kaizen notes

This makes source work reusable across sessions.

Evidence Display In Agent Loop Context

Source visibility should connect to MWMS Agent Loop Context Schema.

Agent loop context should track:

selected sources
inspected sources
source summaries
evidence items
evidence sufficiency
source conflicts
answer readiness

This helps the Next Action Picker decide whether to continue, answer, or escalate.

Evidence Display In Observability

Source visibility should connect to MWMS AI Observability Metadata Standard.

Observability should record:

source count
inspected source count
failed source inspections
source trust rating
source freshness rating
source used in answer
source conflict status
evidence sufficiency

This gives HeadOffice visibility into source quality across AI Employees.

Evidence Display In Evaluation Scorecards

Source visibility supports MWMS AI Employee Evaluation Scorecard Standard.

Source display helps evaluate:

source quality
freshness
factuality
answer relevancy
confidence calibration
decision usefulness
traceability
safety

If source display is weak, evaluation quality is weaker.

Source Display And Confidence

Confidence must reflect evidence quality.

Confidence should be reduced when:

sources are low trust
source freshness is unknown
no official source was found
sources conflict
source inspection failed
evidence is indirect
only commercial sources were used
only user-generated sources were used
source summaries are incomplete
final answer relies on assumptions

Rule

A high-confidence answer requires visible, sufficient evidence.

Source Display And Human Review

Human review should be triggered when:

source evidence is weak
sources conflict
freshness is unknown on a current topic
only low-trust sources are available
source inspection fails
final answer affects compliance
final answer affects budget
final answer affects campaign launch
final answer is client-facing
evidence is insufficient for the decision

The review panel should show the sources that caused concern.

Source Display And Kaizen

Weak source visibility should create Kaizen learning.

Kaizen notes may include:

source type classification missing
freshness not captured
trust rating missing
source summary too vague
source conflict not shown
source used in answer not marked
evidence sufficiency unclear
source UI hard to review
operator could not tell why answer was trusted

These can become future improvements or regression tests.

Source Display Failure Conditions

Source visibility should be marked failed or weak if:

sources were used but not displayed
source URLs are missing
source titles are missing
source summaries are missing
freshness is missing where required
trust rating is missing where required
source conflict is hidden
source inspection failed but answer appears confident
final answer cites evidence that is not stored
source list is too vague to audit
operator cannot tell which source supported which claim

Minimum Starting Implementation

MWMS does not need a perfect source display UI immediately.

Minimum starting source display should include:

source title
source URL or source record ID
source type
retrieved date
evidence summary
freshness rating where relevant
trust rating where relevant
used in final answer yes/no
source inspection status

This is enough to move from hidden evidence to visible evidence.

Recommended Source Display Object

{
  "source_id": "",
  "source_title": "",
  "source_url": "",
  "source_type": "",
  "source_owner": "",
  "publication_date": "",
  "last_updated_date": "",
  "retrieved_at": "",
  "freshness_rating": "",
  "trust_rating": "",
  "relevance_rating": "",
  "evidence_summary": "",
  "key_claims": [],
  "limitations": [],
  "used_in_final_output": false,
  "conflict_detected": false,
  "source_status": ""
}

This is a conceptual object only.

Exact implementation can be adapted later.

Relationship To Research Planning And Query Rewriting

Research planning defines what sources should be found.

Source visibility shows what sources were actually found and used.

The research plan may say:

Find official Google Ads policy source.

Source visibility should show:

whether that source was found
whether it was inspected
whether it was current
whether it supported the answer

This closes the loop between planning and evidence.

Relationship To Search Scrape Summarise Pipeline

This standard points toward a future MWMS Search Scrape Summarise Evidence Pipeline Standard.

That future standard would define the operational pipeline for:

searching
inspecting
summarising
storing
rating
displaying evidence

This page defines the display and governance expectations.

Relationship To Guardrail And Preflight Checks

The AI Guardrail And Preflight Check Standard decides whether sources are required before work begins.

This page defines how those sources should be displayed once used.

Relationship:

Preflight decides:

Are sources required?

Research planning decides:

What sources should we look for?

Source visibility decides:

What sources did we use, and are they good enough?

Future Enhancements

Future enhancements may include:

MWMS Search Scrape Summarise Evidence Pipeline Standard
MWMS Deep Search Source Record Standard
MWMS Source Summary Record Schema
MWMS Evidence Sufficiency Scorecard
MWMS Source Display UI Component Specification
MWMS HeadOffice Evidence Review Panel Specification
MWMS Client Facing Evidence Display Standard
MWMS Research Brain Source Library
MWMS Source Conflict Resolution Standard

These should be created only when implementation or system complexity justifies them.

Drift Protection

This standard prevents the following drift:

hiding sources from operators
treating links as enough evidence
showing citations without trust context
using stale sources without warning
using commercial sources as proof
ignoring source conflicts
hiding failed source inspection
giving high confidence with weak evidence
separating final answers from supporting evidence
making research impossible to audit
making client-facing outputs hard to trust
losing source quality signals from AI work sessions

If sources matter, they must be visible.

If evidence is weak, the operator must be able to see why.

Architectural Intent

The architectural intent of this standard is to make MWMS evidence-first.

MWMS is not building AI Employees that simply answer.

MWMS is building AI Employees that show their work.

For MWMS to trust AI-generated intelligence, the system must display the evidence behind the answer in a way that humans can inspect, review, and improve.

Source visibility turns AI research into operational intelligence.

It makes the system more trustworthy, more auditable, more useful, and more ready for future client-facing delivery.

Change Log

v1.0 Initial Draft

Created the MWMS Source Visibility And Evidence Display Standard based on absorbed insights from the final block of Matt Pocock AIhero Build DeepSearch In TypeScript.

Integrated principles from course sections covering:

showing sources in the frontend
source-backed Deep Search answers
evidence display for operators
source trust and freshness visibility
evidence sufficiency
source conflict awareness
source display in AI work sessions
source visibility as distinct from backend observability
source display as a trust and review layer

Established this standard as the MWMS governance page for displaying source evidence, source quality, source freshness, source limitations, and source support status to human operators.System: MWMS
Document Type: Standard
Status: Draft For MCR
Authority: HeadOffice
Applies To: Research Brain, Affiliate Brain, Ads Brain, Content Brain, HeadOffice Intelligence, Data Brain, Experimentation Brain, Risk Brain, AI Employees, Deep Search Workflows, Future Client Facing AI Systems
Primary Location: MCR
Future Operational Destination: mwmsbrain.site, mwmsheadofficebrain.site, Brain Room, Research Brain, Affiliate Brain, Ads Brain, AI Employee Dashboards, HeadOffice Dashboards, Future Client Portals
Parent Page: HeadOffice
Source Of Truth: MCR
Related Frameworks: MWMS Deep Search Quality And Observability Framework, MWMS Research Planning And Query Rewriting Standard, MWMS AI Guardrail And Preflight Check Standard, MWMS AI Work Session Persistence Standard, MWMS AI Observability Metadata Standard, MWMS AI Employee Evaluation Scorecard Standard, MWMS Agent Loop Control Framework
Course Source: Matt Pocock AIhero Build DeepSearch In TypeScript
Absorption Status: Approved For Integration

Purpose

The purpose of this standard is to define how MWMS displays sources, evidence, and source confidence to human operators.

MWMS AI Employees must not only produce answers.

They must show what evidence was used, where it came from, how reliable it appears, how fresh it is, and whether it supports the final decision.

This standard ensures source evidence is not hidden inside backend traces, raw logs, or model reasoning.

The operator should be able to see:

which sources were used
which sources were inspected
which sources were ignored
what each source contributed
whether sources were current
whether sources were reliable
whether sources conflicted
whether the final answer was properly supported

The goal is to make AI-generated intelligence easier to trust, review, audit, and improve.

Scope

This standard applies to any MWMS workflow where sources, evidence, research, or external information influence an output or decision.

This includes:

Deep Search workflows
Research Brain investigations
Affiliate Brain offer evaluations
Ads Brain compliance reviews
Content Brain research workflows
HeadOffice Intelligence reviews
Newsletter Intelligence follow-up research
Product or vendor research
Tool evaluations
Source inspections
Market trend research
Compliance and policy checks
Experimentation Brain analysis
Risk Brain reviews
Future client-facing AIBS research outputs

This standard does not define exact frontend code, React components, scraping implementation, or source database table structure.

It defines the MWMS governance standard for showing evidence to operators.

Core Rule

The core rule is:

Sources used by AI Employees should be visible to the operator, not hidden only in backend trace logs.

If an AI Employee uses sources to support an answer, the operator should be able to inspect the evidence behind that answer.

A source-backed answer without visible source evidence is incomplete.

Definition Of Source Visibility

Source visibility means the human operator can see the source evidence behind an AI output.

Source visibility should answer:

What sources did the AI use?
What sources were inspected?
What did each source say?
Was the source official, expert, commercial, user-generated, or unknown?
Was the source current enough?
Was the source trusted?
Was the source actually used in the final answer?
Did any source conflict with another?
Did the AI answer rely on strong or weak evidence?

Source visibility turns AI output from a black-box answer into a reviewable intelligence record.

Definition Of Evidence Display

Evidence display is the user-facing presentation of the source material, evidence summaries, trust indicators, freshness indicators, and support status behind an AI answer.

Evidence display may appear as:

source cards
evidence panels
expandable source lists
citation rows
source summaries
trust and freshness badges
source conflict warnings
evidence sufficiency notes
final answer support map
HeadOffice review panels

Evidence display is not the same as raw logs.

It should be readable, structured, and useful to the operator.

Why MWMS Needs This Standard

Without source visibility, MWMS risks:

trusting polished but unsupported answers
missing outdated sources
missing weak evidence
hiding source conflicts
making poor affiliate decisions
making risky ad compliance decisions
approving weak content
repeating research
losing auditability
weakening HeadOffice oversight
making AI Employees harder to evaluate
making future client-facing systems less trustworthy

With source visibility, MWMS gains:

operator trust
better review quality
stronger evidence discipline
better compliance safety
better Research Brain outputs
better Affiliate Brain offer decisions
better Ads Brain policy review
better HeadOffice intelligence
reusable source records
clearer Kaizen learning

Source Visibility Versus Observability

Observability is for tracing what the system did.

Source visibility is for showing the operator what evidence supports the answer.

Observability	Source Visibility
backend trace	operator-facing evidence view
model actions	source evidence
tool activity	source cards
database actions	source summaries
cost and latency	trust/freshness indicators
debugging	review and decision support

Both are needed.

A backend trace may show that a source was inspected.

Source visibility shows whether that source was useful, current, trusted, and relevant.

Source Visibility Versus Citations

Citations show where information came from.

Source visibility shows whether the source is useful and trustworthy.

A citation alone is not enough.

MWMS should aim to show:

source title
source URL
source type
source date
retrieved date
trust rating
freshness rating
evidence summary
relevance to task
used in final answer yes/no
limitations or conflicts

A link without source context is weak evidence display.

Required Source Display Fields

Each displayed source should include, where available:

Field	Description
source_title	Human-readable title
source_url	Source link or source record reference
source_type	Official, expert, commercial, user-generated, unknown
source_owner	Vendor, platform, publication, user, organisation
publication_date	Date published if visible
last_updated_date	Date updated if visible
retrieved_at	Date/time MWMS retrieved it
freshness_rating	Current, acceptable, possibly outdated, outdated, unknown
trust_rating	High, medium, low, unknown
relevance_rating	High, medium, low
evidence_summary	What useful evidence the source provided
key_claims	Main claims or facts extracted
limitations	What the source does not prove
used_in_final_output	Yes or no
conflict_detected	Yes or no
source_status	Inspected, not inspected, failed, blocked, ignored

Recommended Source Card Format

A source card should be readable at a glance.

Recommended format:

Source Title:
[Title]

Source Type:
Official / Expert / Commercial / User-Generated / Unknown

Freshness:
Current / Acceptable / Possibly Outdated / Outdated / Unknown

Trust:
High / Medium / Low / Unknown

Evidence Summary:
[Short summary of what this source contributed]

Used In Final Answer:
Yes / No

Limitations:
[What this source does not prove or where caution is needed]

This can later become a UI component on mwmsbrain.site or mwmsheadofficebrain.site.

Source Type Classification

MWMS should classify source types.

Official Source

Examples:

vendor documentation
official product page
platform policy page
government page
company announcement
official changelog
affiliate network page

Default trust level: high, but still checked for bias and freshness.

Expert Source

Examples:

respected industry publication
specialist blog
analyst report
credible technical article
recognised practitioner source

Default trust level: medium to high.

Commercial Source

Examples:

sales page
affiliate review page
comparison page with commissions
agency landing page
vendor marketing page

Default trust level: medium to low unless corroborated.

User-Generated Source

Examples:

Reddit
forums
comments
social media posts
community discussion

Default trust level: signal only, not proof.

Unknown Source

Examples:

content farms
anonymous blogs
scraped reposts
pages with unclear ownership
thin AI-generated content

Default trust level: low.

Freshness Display Standard

Every source used in time-sensitive workflows should show freshness.

Freshness ratings:

Rating	Meaning
Current	Suitable for current decision-making
Acceptable	Recent enough for the task
Possibly Outdated	Use with caution
Outdated	Should not be trusted for current decisions
Unknown	No clear date or freshness signal
Not Applicable	Evergreen or historical source

Freshness matters most for:

pricing
affiliate payouts
product availability
platform policies
laws and regulations
AI tool features
software documentation
advertising rules
market trends
current events
compliance matters

Rule

If freshness matters and the source date is unknown, the source should not be displayed as high confidence.

Trust Display Standard

Sources should display a trust rating where possible.

Trust ratings:

Rating	Meaning
High	Official, credible, directly relevant, low bias
Medium	Useful but may require corroboration
Low	Weak, biased, indirect, outdated, or questionable
Unknown	Not enough information to judge

Trust rating should consider:

source owner
source type
publication quality
bias
commercial incentive
directness of evidence
freshness
corroboration
history of reliability

Rule

A low-trust source may be shown as a signal, but should not be treated as proof.

Relevance Display Standard

A source should show how relevant it is to the task.

Relevance ratings:

Rating	Meaning
High	Directly answers or supports the task
Medium	Supports part of the task
Low	Background only or weakly related

A source can be trustworthy but not relevant.

A source can be relevant but not trustworthy.

Both must be visible.

Evidence Summary Rule

Each source should include a short evidence summary.

The summary should answer:

What did this source contribute?
What claim or fact did it support?
Why was it useful?
What limitation should the operator know?

The summary must not invent missing evidence.

If the source does not answer the needed question, the summary should say so.

Used In Final Output Rule

MWMS should show whether a source was actually used in the final answer.

Possible statuses:

Status	Meaning
Used	Source supported final answer
Not Used	Source inspected but not used
Background Only	Helped context but not final claim
Rejected	Source was weak, irrelevant, or unreliable
Failed	Source could not be inspected
Conflicting	Source conflicted with other evidence

This helps operators understand the evidence path.

Source Conflict Display Rule

If sources conflict, the operator should see it.

Conflict display should include:

conflicting sources
what they disagree on
which source appears stronger
whether the conflict affects confidence
whether human review is required

Rule

Source conflict should lower confidence unless resolved.

The AI Employee should not hide disagreement between sources.

Evidence Sufficiency Display

The final output should include an evidence sufficiency rating where relevant.

Suggested ratings:

Rating	Meaning
Strong	Evidence is reliable, current, and directly supports answer
Acceptable	Evidence supports answer but has minor limitations
Weak	Evidence is incomplete, indirect, old, or uncertain
Insufficient	Not enough evidence to support a trusted answer

Evidence sufficiency should influence:

confidence score
human review requirement
final recommendation
whether the workflow continues
whether the result is parked or escalated

Source Display By Workflow Type

Different workflows require different source display depth.

Deep Search

Should show:

all inspected sources
evidence summaries
trust/freshness ratings
used-in-answer status
conflicts
evidence sufficiency

Affiliate Offer Evaluation

Should show:

vendor/product source
affiliate network source
customer complaint/review signals
competitor sources
compliance/policy sources where relevant
payout or terms source if available

Ads Compliance Review

Should show:

official policy source
product claim source
compliance risk evidence
jurisdiction source if relevant
source freshness

Content Research

Should show:

topic sources
competing content
authority sources
freshness rating
search intent evidence

HeadOffice Intelligence

Should show:

original newsletter/source
supporting external sources if researched
business relevance evidence
routing basis
risk/confidence notes

Client-Facing Output

Should show sources carefully, with privacy and simplicity controls.

Client-facing source display may be simplified, but internal evidence must remain available.

Operator UI Source Panel

Future MWMS interfaces should include an operator source panel where useful.

A source panel may include:

source list
source cards
filters by type/trust/freshness
used versus unused sources
conflicts
evidence summary
source inspection status
open source link
copy source summary
create source record
route source issue to Research Brain
mark source as weak
add human review note

This is especially valuable for HeadOffice, Research Brain, Affiliate Brain, and Ads Brain.

Source Visibility Levels

Not all users need the same source visibility.

Suggested visibility levels:

Level	Meaning
Internal Full Evidence	Full source detail for MWMS operators
HeadOffice Review	Evidence plus risk/confidence indicators
Developer Debug	Source plus retrieval/tool metadata
Client Summary	Simplified sources and explanation
Hidden/Internal Only	Sensitive sources not shown to client
Archived Evidence	Historical source record kept for audit

Rule

Internal MWMS evidence should be richer than client-facing evidence.

Source Privacy And Safety Rule

Source display must not expose sensitive information unnecessarily.

Do not expose:

private credentials
private user data
restricted client data
internal API responses
private financial details
confidential source excerpts
copyrighted long-form content beyond what is allowed
private email content unless authorised

Where needed, display:

source reference
short summary
redacted excerpt
internal-only tag
access-restricted link

Evidence Display In AI Work Sessions

Source visibility should connect to MWMS AI Work Session Persistence Standard.

A persistent AI work session should store:

source IDs
source summaries
source ratings
evidence sufficiency
sources used in final answer
conflicts detected
review notes
source-related Kaizen notes

This makes source work reusable across sessions.

Evidence Display In Agent Loop Context

Source visibility should connect to MWMS Agent Loop Context Schema.

Agent loop context should track:

selected sources
inspected sources
source summaries
evidence items
evidence sufficiency
source conflicts
answer readiness

This helps the Next Action Picker decide whether to continue, answer, or escalate.

Evidence Display In Observability

Source visibility should connect to MWMS AI Observability Metadata Standard.

Observability should record:

source count
inspected source count
failed source inspections
source trust rating
source freshness rating
source used in answer
source conflict status
evidence sufficiency

This gives HeadOffice visibility into source quality across AI Employees.

Evidence Display In Evaluation Scorecards

Source visibility supports MWMS AI Employee Evaluation Scorecard Standard.

Source display helps evaluate:

source quality
freshness
factuality
answer relevancy
confidence calibration
decision usefulness
traceability
safety

If source display is weak, evaluation quality is weaker.

Source Display And Confidence

Confidence must reflect evidence quality.

Confidence should be reduced when:

sources are low trust
source freshness is unknown
no official source was found
sources conflict
source inspection failed
evidence is indirect
only commercial sources were used
only user-generated sources were used
source summaries are incomplete
final answer relies on assumptions

Rule

A high-confidence answer requires visible, sufficient evidence.

Source Display And Human Review

Human review should be triggered when:

source evidence is weak
sources conflict
freshness is unknown on a current topic
only low-trust sources are available
source inspection fails
final answer affects compliance
final answer affects budget
final answer affects campaign launch
final answer is client-facing
evidence is insufficient for the decision

The review panel should show the sources that caused concern.

Source Display And Kaizen

Weak source visibility should create Kaizen learning.

Kaizen notes may include:

source type classification missing
freshness not captured
trust rating missing
source summary too vague
source conflict not shown
source used in answer not marked
evidence sufficiency unclear
source UI hard to review
operator could not tell why answer was trusted

These can become future improvements or regression tests.

Source Display Failure Conditions

Source visibility should be marked failed or weak if:

sources were used but not displayed
source URLs are missing
source titles are missing
source summaries are missing
freshness is missing where required
trust rating is missing where required
source conflict is hidden
source inspection failed but answer appears confident
final answer cites evidence that is not stored
source list is too vague to audit
operator cannot tell which source supported which claim

Minimum Starting Implementation

MWMS does not need a perfect source display UI immediately.

Minimum starting source display should include:

source title
source URL or source record ID
source type
retrieved date
evidence summary
freshness rating where relevant
trust rating where relevant
used in final answer yes/no
source inspection status

This is enough to move from hidden evidence to visible evidence.

Recommended Source Display Object

{
  "source_id": "",
  "source_title": "",
  "source_url": "",
  "source_type": "",
  "source_owner": "",
  "publication_date": "",
  "last_updated_date": "",
  "retrieved_at": "",
  "freshness_rating": "",
  "trust_rating": "",
  "relevance_rating": "",
  "evidence_summary": "",
  "key_claims": [],
  "limitations": [],
  "used_in_final_output": false,
  "conflict_detected": false,
  "source_status": ""
}

This is a conceptual object only.

Exact implementation can be adapted later.

Relationship To Research Planning And Query Rewriting

Research planning defines what sources should be found.

Source visibility shows what sources were actually found and used.

The research plan may say:

Find official Google Ads policy source.

Source visibility should show:

whether that source was found
whether it was inspected
whether it was current
whether it supported the answer

This closes the loop between planning and evidence.

Relationship To Search Scrape Summarise Pipeline

This standard points toward a future MWMS Search Scrape Summarise Evidence Pipeline Standard.

That future standard would define the operational pipeline for:

searching
inspecting
summarising
storing
rating
displaying evidence

This page defines the display and governance expectations.

Relationship To Guardrail And Preflight Checks

The AI Guardrail And Preflight Check Standard decides whether sources are required before work begins.

This page defines how those sources should be displayed once used.

Relationship:

Preflight decides:

Are sources required?

Research planning decides:

What sources should we look for?

Source visibility decides:

What sources did we use, and are they good enough?

Future Enhancements

Future enhancements may include:

MWMS Search Scrape Summarise Evidence Pipeline Standard
MWMS Deep Search Source Record Standard
MWMS Source Summary Record Schema
MWMS Evidence Sufficiency Scorecard
MWMS Source Display UI Component Specification
MWMS HeadOffice Evidence Review Panel Specification
MWMS Client Facing Evidence Display Standard
MWMS Research Brain Source Library
MWMS Source Conflict Resolution Standard

These should be created only when implementation or system complexity justifies them.

Drift Protection

This standard prevents the following drift:

hiding sources from operators
treating links as enough evidence
showing citations without trust context
using stale sources without warning
using commercial sources as proof
ignoring source conflicts
hiding failed source inspection
giving high confidence with weak evidence
separating final answers from supporting evidence
making research impossible to audit
making client-facing outputs hard to trust
losing source quality signals from AI work sessions

If sources matter, they must be visible.

If evidence is weak, the operator must be able to see why.

Architectural Intent

The architectural intent of this standard is to make MWMS evidence-first.

MWMS is not building AI Employees that simply answer.

MWMS is building AI Employees that show their work.

For MWMS to trust AI-generated intelligence, the system must display the evidence behind the answer in a way that humans can inspect, review, and improve.

Source visibility turns AI research into operational intelligence.

It makes the system more trustworthy, more auditable, more useful, and more ready for future client-facing delivery.

Change Log

v1.0 Initial Draft

Created the MWMS Source Visibility And Evidence Display Standard based on absorbed insights from the final block of Matt Pocock AIhero Build DeepSearch In TypeScript.

Integrated principles from course sections covering:

showing sources in the frontend
source-backed Deep Search answers
evidence display for operators
source trust and freshness visibility
evidence sufficiency
source conflict awareness
source display in AI work sessions
source visibility as distinct from backend observability
source display as a trust and review layer

Established this standard as the MWMS governance page for displaying source evidence, source quality, source freshness, source limitations, and source support status to human operators.