Below is a single, exhaustive build prompt you can give to an AI coding assistant to add a “provocation / reviewer-question engine” to SOO-Wizard, implemented using browser-side AI (Chrome Built-in AI when available), explicitly modeled as a question generator, not an answer engine.
This prompt is written to preserve the discipline and intent of SOO-Wizard and to avoid turning it into a chat toy, a content generator, or a faux expert system.
Exhaustive build prompt
Feature: Reviewer Question Engine (WWSD-style, Question-Only AI)
You are working in the repository SOO-Wizard. Add a feature that uses browser-based AI to generate structured, evidence-based questions that a thoughtful reviewer would ask about a Statement of Objectives, scope definition, or service description.
This feature must behave like a disciplined provocation engine, not a conversational assistant.
Core intent (do not deviate)
The AI’s role is:
To surface unanswered decisions, ambiguities, and missing intent by asking the right questions.
It must never:
answer the questions
invent requirements
interpret policy
provide recommendations disguised as questions
generate content to fill gaps
This tool exists to slow authors down in productive ways.
Mental model (must be preserved)
This feature implements a “what would a good reviewer ask here?” pattern.
Not:
“what should we do?”
“how can we improve this?”
But:
“what decision has not been made yet?”
“what assumption is implicit but unstated?”
“what would cause confusion, risk, or rework later?”
User-facing behavior
Feature name (working)
Use neutral, sober language such as:
“Reviewer questions”
“Unanswered decisions”
“Questions to resolve”
Do not reference:
Seth Godin
personas
experts
authority figures
When the feature is invoked
The tool may be triggered:
manually (“Generate reviewer questions”)
at defined checkpoints (e.g. before export)
per section, not just globally
It must never run automatically without user intent.
Inputs to the AI (strictly bounded)
The AI does not see raw documents or freeform text dumps.
You must construct a structured context object and pass only that.
Required inputs
Document title
Declared purpose (if present)
Scope summary (if present)
Section list:
section title
section intent/purpose (if present)
short text summary (trimmed, plain text)
Component inventory per section:
form
submission action
review/approval step
data collection
external dependency
accessibility-critical elements (forms, tables, navigation)
Known constraints:
government / public sector
procurement / contract context
accessibility required
security/privacy sensitivity (boolean flags)
Do not pass:
full prose
HTML
policy documents
code
Question categories (fixed taxonomy)
All questions must be tagged with one and only one category.
- Purpose and scope
Questions about why this exists and what it covers.
Examples:
“What decision should the reader be able to make after this section?”
“What is explicitly out of scope, and where is that stated?”
- User task and flow
Questions about what the user does and what happens next.
Examples:
“What happens after this step is completed?”
“Is there a point where users commonly need help or clarification?”
- Accessibility and inclusion
Questions automation cannot fully answer.
Examples:
“How are errors communicated to assistive technology users?”
“Does this interaction rely on visual cues alone?”
- Content clarity and plain language
Questions about comprehension and ambiguity.
Examples:
“Are any terms used here likely to be unfamiliar to a first-time user?”
“Is this instruction actionable without prior knowledge?”
- Trust, risk, and policy
Questions about obligations and consequences.
Examples:
“Is this requirement driven by policy or by design choice?”
“Should users be informed about data retention or review timelines?”
- Ownership and accountability
Questions about responsibility.
Examples:
“Who is responsible for maintaining this content over time?”
“What happens if this process fails or is delayed?”
Question generation rules (critical)
The AI must follow all of these rules:
Questions only
No answers
No suggestions framed as questions
No implied solutions
Evidence-triggered
Each question must be traceable to:
a missing field
a present component
a structural gap
No generic “Have you considered…” questions
Actionable
A human should be able to answer the question concretely
The answer should result in a change to the SOO or scope
Non-duplicative
Do not ask the same question in different wording
Respect scope
If something is explicitly marked “out of scope”, do not question it
Output format (strict)
The AI must return valid JSON only, matching this shape:
{ "questions": [ { "id": "Q-001", "category": "user-task", "question": "What happens after the user submits this information?", "severity": "high", "trigger": "submission-action-without-next-step" } ] }
Field definitions
id: stable identifier (you may generate this)
category: one of the fixed taxonomy values
question: plain language, concise
severity: high | medium | low
trigger: short machine-readable explanation of why this question was asked
Severity model
High: blocking ambiguity; likely to cause rework or failure
Medium: important but not blocking
Low: refinement or clarity improvement
Severity must be defensible.
UI behavior
Questions are displayed as a checklist
Each question can be:
marked “answered”
marked “not applicable”
deferred
No inline answering in the AI panel
Authors must edit the document to resolve questions
Optional:
Link questions to the section they apply to
Browser AI constraints
Use Chrome Built-in AI if available
If unavailable:
disable the feature
explain why clearly
No server fallback by default
All processing must be local.
Safety and ethics constraints
Do not present the AI as authoritative
Do not imply compliance
Do not claim completeness
Display a disclaimer:
“These questions highlight potential gaps. They do not replace human review.”
Code structure (required)
Add clear separation:
ai/context-builder.js – builds structured input
ai/prompts/reviewer-questions.js – single source of prompt truth
ai/run.js – execution and validation
ui/questions-panel.js – rendering and interaction
validation/schema.js – output validation
Do not embed prompts directly in UI code.
Documentation updates (required)
Add a section: “Reviewer Questions (AI-assisted)”
Explain:
purpose of the feature
what it does not do
how it supports SOO quality
privacy and local execution
Acceptance criteria
The tool generates only questions, never answers.
Questions are tied to document structure.
Authors remain responsible for decisions.
No content is invented.
Feature aligns with SOO-Wizard’s existing philosophy.
Tool works entirely client-side or fails gracefully.
Explicit non-goals (do not implement)
No chat interface
No persona simulation
No auto-generation of scope language
No policy interpretation
No scoring or “grade”
Final note to implementer
This feature is successful only if authors feel challenged, not assisted.
If it makes writing feel easier without forcing decisions, it has failed.
If you want, next I can:
write the exact reviewer-question prompt text
map question triggers to SOO-Wizard’s existing data model
help you name and position this feature so it survives scrutiny in procurement and government contexts
Below is a single, exhaustive build prompt you can give to an AI coding assistant to add a “provocation / reviewer-question engine” to SOO-Wizard, implemented using browser-side AI (Chrome Built-in AI when available), explicitly modeled as a question generator, not an answer engine.
This prompt is written to preserve the discipline and intent of SOO-Wizard and to avoid turning it into a chat toy, a content generator, or a faux expert system.
Exhaustive build prompt
Feature: Reviewer Question Engine (WWSD-style, Question-Only AI)
You are working in the repository SOO-Wizard. Add a feature that uses browser-based AI to generate structured, evidence-based questions that a thoughtful reviewer would ask about a Statement of Objectives, scope definition, or service description.
This feature must behave like a disciplined provocation engine, not a conversational assistant.
Core intent (do not deviate)
The AI’s role is:
To surface unanswered decisions, ambiguities, and missing intent by asking the right questions.
It must never:
answer the questions
invent requirements
interpret policy
provide recommendations disguised as questions
generate content to fill gaps
This tool exists to slow authors down in productive ways.
Mental model (must be preserved)
This feature implements a “what would a good reviewer ask here?” pattern.
Not:
“what should we do?”
“how can we improve this?”
But:
“what decision has not been made yet?”
“what assumption is implicit but unstated?”
“what would cause confusion, risk, or rework later?”
User-facing behavior
Feature name (working)
Use neutral, sober language such as:
“Reviewer questions”
“Unanswered decisions”
“Questions to resolve”
Do not reference:
Seth Godin
personas
experts
authority figures
When the feature is invoked
The tool may be triggered:
manually (“Generate reviewer questions”)
at defined checkpoints (e.g. before export)
per section, not just globally
It must never run automatically without user intent.
Inputs to the AI (strictly bounded)
The AI does not see raw documents or freeform text dumps.
You must construct a structured context object and pass only that.
Required inputs
Document title
Declared purpose (if present)
Scope summary (if present)
Section list:
section title
section intent/purpose (if present)
short text summary (trimmed, plain text)
Component inventory per section:
form
submission action
review/approval step
data collection
external dependency
accessibility-critical elements (forms, tables, navigation)
Known constraints:
government / public sector
procurement / contract context
accessibility required
security/privacy sensitivity (boolean flags)
Do not pass:
full prose
HTML
policy documents
code
Question categories (fixed taxonomy)
All questions must be tagged with one and only one category.
Questions about why this exists and what it covers.
Examples:
“What decision should the reader be able to make after this section?”
“What is explicitly out of scope, and where is that stated?”
Questions about what the user does and what happens next.
Examples:
“What happens after this step is completed?”
“Is there a point where users commonly need help or clarification?”
Questions automation cannot fully answer.
Examples:
“How are errors communicated to assistive technology users?”
“Does this interaction rely on visual cues alone?”
Questions about comprehension and ambiguity.
Examples:
“Are any terms used here likely to be unfamiliar to a first-time user?”
“Is this instruction actionable without prior knowledge?”
Questions about obligations and consequences.
Examples:
“Is this requirement driven by policy or by design choice?”
“Should users be informed about data retention or review timelines?”
Questions about responsibility.
Examples:
“Who is responsible for maintaining this content over time?”
“What happens if this process fails or is delayed?”
Question generation rules (critical)
The AI must follow all of these rules:
Questions only
No answers
No suggestions framed as questions
No implied solutions
Evidence-triggered
Each question must be traceable to:
a missing field
a present component
a structural gap
No generic “Have you considered…” questions
Actionable
A human should be able to answer the question concretely
The answer should result in a change to the SOO or scope
Non-duplicative
Do not ask the same question in different wording
Respect scope
If something is explicitly marked “out of scope”, do not question it
Output format (strict)
The AI must return valid JSON only, matching this shape:
{ "questions": [ { "id": "Q-001", "category": "user-task", "question": "What happens after the user submits this information?", "severity": "high", "trigger": "submission-action-without-next-step" } ] }
Field definitions
id: stable identifier (you may generate this)
category: one of the fixed taxonomy values
question: plain language, concise
severity: high | medium | low
trigger: short machine-readable explanation of why this question was asked
Severity model
High: blocking ambiguity; likely to cause rework or failure
Medium: important but not blocking
Low: refinement or clarity improvement
Severity must be defensible.
UI behavior
Questions are displayed as a checklist
Each question can be:
marked “answered”
marked “not applicable”
deferred
No inline answering in the AI panel
Authors must edit the document to resolve questions
Optional:
Link questions to the section they apply to
Browser AI constraints
Use Chrome Built-in AI if available
If unavailable:
disable the feature
explain why clearly
No server fallback by default
All processing must be local.
Safety and ethics constraints
Do not present the AI as authoritative
Do not imply compliance
Do not claim completeness
Display a disclaimer:
“These questions highlight potential gaps. They do not replace human review.”
Code structure (required)
Add clear separation:
ai/context-builder.js – builds structured input
ai/prompts/reviewer-questions.js – single source of prompt truth
ai/run.js – execution and validation
ui/questions-panel.js – rendering and interaction
validation/schema.js – output validation
Do not embed prompts directly in UI code.
Documentation updates (required)
Add a section: “Reviewer Questions (AI-assisted)”
Explain:
purpose of the feature
what it does not do
how it supports SOO quality
privacy and local execution
Acceptance criteria
The tool generates only questions, never answers.
Questions are tied to document structure.
Authors remain responsible for decisions.
No content is invented.
Feature aligns with SOO-Wizard’s existing philosophy.
Tool works entirely client-side or fails gracefully.
Explicit non-goals (do not implement)
No chat interface
No persona simulation
No auto-generation of scope language
No policy interpretation
No scoring or “grade”
Final note to implementer
This feature is successful only if authors feel challenged, not assisted.
If it makes writing feel easier without forcing decisions, it has failed.
If you want, next I can:
write the exact reviewer-question prompt text
map question triggers to SOO-Wizard’s existing data model
help you name and position this feature so it survives scrutiny in procurement and government contexts