now-assist-qa

Now Assist Q&A Configuration

Overview

This skill covers configuring ServiceNow Now Assist Q&A for conversational AI assistance:

Setting up Now Assist skills for Q&A across different contexts (agent, employee, developer)
Configuring knowledge sources that feed conversational responses
Tuning response quality through prompt engineering and LLM parameters
Managing conversation context and multi-turn dialogue
Deploying Now Assist panels in Workspace, Portal, and Mobile
Monitoring response quality through feedback analysis
Integrating with AI Search for retrieval-augmented answers

When to use: When enabling AI-powered Q&A for agents, employees, or customers through Now Assist, configuring knowledge-grounded responses, or tuning conversational AI quality.

Prerequisites

Roles: now_assist_admin, admin
Plugins: sn_now_assist (Now Assist), com.snc.generative_ai_controller (Generative AI Controller), sn_gen_ai (Generative AI)
Access: sn_now_assist_skill, sn_now_assist_skill_config, sn_gen_ai_config tables
Knowledge: Understanding of LLM concepts (prompts, temperature, tokens), knowledge management
Related Skills: genai/ai-search-rag for search configuration, genai/skill-kit-custom for custom skills

Procedure

Step 1: Assess Current Now Assist Configuration

Query existing Now Assist skills and their status.

MCP Approach:

Use SN-Query-Table on sn_now_assist_skill:
  - query: active=true
  - fields: sys_id,name,description,skill_type,context,active,status
  - limit: 20

Check existing skill configurations:

Use SN-Query-Table on sn_now_assist_skill_config:
  - query: active=true
  - fields: sys_id,skill,name,config_type,value
  - limit: 50

REST Approach:

GET /api/now/table/sn_now_assist_skill
  ?sysparm_query=active=true
  &sysparm_fields=sys_id,name,description,skill_type,context,active
  &sysparm_limit=20

Step 2: Configure Now Assist Q&A Skill

Agent-Facing Q&A Skill:

MCP Approach:

Use SN-Create-Record on sn_now_assist_skill:
  - name: "IT Agent Q&A"
  - description: "Provides AI-powered answers to IT agent questions from knowledge bases and resolved incidents"
  - skill_type: "qa"
  - context: "agent_workspace"
  - active: true
  - status: "draft"
  - knowledge_sources: "<kb_sys_id_1>,<kb_sys_id_2>"
  - enable_rag: true
  - response_mode: "generative"

REST Approach:

POST /api/now/table/sn_now_assist_skill
Body: {
  "name": "IT Agent Q&A",
  "description": "Provides AI-powered answers to IT agent questions from knowledge bases",
  "skill_type": "qa",
  "context": "agent_workspace",
  "active": true,
  "status": "draft",
  "enable_rag": true,
  "response_mode": "generative"
}

Employee-Facing Q&A Skill:

Use SN-Create-Record on sn_now_assist_skill:
  - name: "Employee Self-Service Q&A"
  - description: "AI answers for common employee IT and HR questions"
  - skill_type: "qa"
  - context: "employee_portal"
  - active: true
  - status: "draft"
  - knowledge_sources: "<it_kb_sys_id>,<hr_kb_sys_id>"
  - enable_rag: true
  - response_mode: "generative"
  - fallback_action: "create_incident"

Context options for Now Assist skills:

Context	Value	Description
Agent Workspace	agent_workspace	IT agents in workspace UI
Employee Portal	employee_portal	Self-service employee portal
Customer Portal	customer_portal	External customer-facing
Mobile	mobile	ServiceNow mobile app
Virtual Agent	virtual_agent	VA conversation channel
Platform	platform	Platform-wide availability

Step 3: Configure Knowledge Sources

Link knowledge bases to the Q&A skill for grounded responses.

MCP Approach:

Use SN-Query-Table on kb_knowledge_base:
  - query: active=true
  - fields: sys_id,title,description,kb_version
  - limit: 20

Associate knowledge bases with the skill:

Use SN-Create-Record on sn_now_assist_skill_config:
  - skill: "<qa_skill_sys_id>"
  - name: "knowledge_source_1"
  - config_type: "knowledge_base"
  - value: "<kb_sys_id>"
  - active: true
  - order: 100

Use SN-Create-Record on sn_now_assist_skill_config:
  - skill: "<qa_skill_sys_id>"
  - name: "knowledge_source_2"
  - config_type: "knowledge_base"
  - value: "<hr_kb_sys_id>"
  - active: true
  - order: 200

Configure knowledge filtering:

Use SN-Create-Record on sn_now_assist_skill_config:
  - skill: "<qa_skill_sys_id>"
  - name: "kb_filter"
  - config_type: "knowledge_filter"
  - value: "workflow_state=published^valid_to>=javascript:gs.now()"
  - active: true

Step 4: Configure LLM Parameters

Set up the generative AI parameters for response generation.

MCP Approach:

Use SN-Create-Record on sn_gen_ai_config:
  - name: "Now Assist Q&A LLM Config"
  - description: "LLM parameters for Now Assist Q&A responses"
  - active: true
  - llm_provider: "now_llm"
  - model: "default"
  - temperature: 0.3
  - max_tokens: 400
  - top_p: 0.9
  - frequency_penalty: 0.1
  - presence_penalty: 0.1

REST Approach:

POST /api/now/table/sn_gen_ai_config
Body: {
  "name": "Now Assist Q&A LLM Config",
  "active": true,
  "llm_provider": "now_llm",
  "temperature": 0.3,
  "max_tokens": 400,
  "top_p": 0.9
}

Link LLM config to skill:

Use SN-Create-Record on sn_now_assist_skill_config:
  - skill: "<qa_skill_sys_id>"
  - name: "llm_config"
  - config_type: "gen_ai_config"
  - value: "<gen_ai_config_sys_id>"
  - active: true

Step 5: Configure System Prompts

System prompts guide LLM behavior for Q&A responses.

MCP Approach:

Use SN-Create-Record on sn_now_assist_skill_config:
  - skill: "<qa_skill_sys_id>"
  - name: "system_prompt"
  - config_type: "prompt"
  - value: |
      You are an IT support assistant for {company_name}. Your role is to help agents
      find answers to technical questions using the provided knowledge base content.

      Guidelines:
      - Only answer based on the provided context. Do not make up information.
      - If the context does not contain a clear answer, say "I don't have enough
        information to answer this question" and suggest creating a knowledge article.
      - Always cite the source knowledge article by title.
      - Keep answers concise and actionable, using bullet points for steps.
      - If the question involves a specific incident, reference relevant fields.
      - Never reveal internal system details, credentials, or sensitive data.
  - active: true

Prompt template variables:

Variable	Description	Example
{company_name}	Customer organization name	Acme Corp
{user_name}	Current user's name	John Smith
{user_role}	Current user's primary role	ITIL Agent
{context_record}	Current record being viewed	INC0012345
{knowledge_context}	Retrieved knowledge content	(injected by RAG)
{conversation_history}	Previous turns in dialogue	(auto-populated)

Step 6: Configure Now Assist Panel

Set up where and how the Now Assist panel appears.

MCP Approach:

Use SN-Create-Record on sn_now_assist_panel_config:
  - name: "Agent Workspace Q&A Panel"
  - description: "Now Assist Q&A panel for IT agent workspace"
  - active: true
  - context: "agent_workspace"
  - skills: "<qa_skill_sys_id>"
  - position: "right_sidebar"
  - auto_open: false
  - show_feedback: true
  - show_sources: true
  - max_conversation_turns: 10
  - greeting_message: "Hi! I can help you find answers from our knowledge base. What would you like to know?"

REST Approach:

POST /api/now/table/sn_now_assist_panel_config
Body: {
  "name": "Agent Workspace Q&A Panel",
  "active": true,
  "context": "agent_workspace",
  "skills": "<qa_skill_sys_id>",
  "position": "right_sidebar",
  "show_feedback": true,
  "show_sources": true
}

Step 7: Configure Conversation Context

Set up how conversation context is managed for multi-turn dialogues.

MCP Approach:

Use SN-Create-Record on sn_now_assist_skill_config:
  - skill: "<qa_skill_sys_id>"
  - name: "context_config"
  - config_type: "context"
  - value: '{
      "max_history_turns": 5,
      "include_record_context": true,
      "record_fields": ["short_description", "description", "priority", "category", "assignment_group"],
      "context_window_tokens": 3000,
      "clear_on_record_change": true
    }'
  - active: true

Step 8: Set Up Response Quality Guardrails

MCP Approach:

Use SN-Create-Record on sn_now_assist_skill_config:
  - skill: "<qa_skill_sys_id>"
  - name: "guardrails"
  - config_type: "safety"
  - value: '{
      "require_knowledge_grounding": true,
      "min_confidence_score": 0.65,
      "block_pii_in_response": true,
      "max_response_length": 500,
      "prohibited_topics": ["salary", "termination", "legal_advice"],
      "fallback_message": "I am not able to answer this question. Please contact your IT service desk for assistance.",
      "enable_content_filtering": true
    }'
  - active: true

Step 9: Activate and Deploy

MCP Approach:

Use SN-Update-Record on sn_now_assist_skill:
  - sys_id: "<qa_skill_sys_id>"
  - status: "published"
  - active: true

Verify configuration is complete:

Use SN-Query-Table on sn_now_assist_skill_config:
  - query: skill=<qa_skill_sys_id>^active=true
  - fields: name,config_type,active
  - limit: 20

Verify panel is active:

Use SN-Query-Table on sn_now_assist_panel_config:
  - query: skills=<qa_skill_sys_id>^active=true
  - fields: name,context,position,active

Step 10: Monitor and Tune Response Quality

Query feedback data:

Use SN-Query-Table on sn_now_assist_feedback:
  - query: skill=<qa_skill_sys_id>^sys_created_on>javascript:gs.daysAgo(7)
  - fields: sys_id,query,response,rating,feedback_text,user
  - limit: 50
  - orderBy: sys_created_on
  - orderDirection: desc

Analyze negative feedback patterns:

Use SN-Query-Table on sn_now_assist_feedback:
  - query: skill=<qa_skill_sys_id>^rating<3
  - fields: query,response,rating,feedback_text
  - limit: 20

Adjust based on feedback:

Use SN-Update-Record on sn_gen_ai_config:
  - sys_id: "<gen_ai_config_sys_id>"
  - temperature: 0.2
  - max_tokens: 500

Tool Usage

Tool	Purpose	When to Use
SN-Query-Table	Find existing skills, configs, feedback	Discovery and monitoring
SN-Create-Record	Create skills, configs, panel settings	Initial setup
SN-Update-Record	Tune LLM params, activate skills	Optimization and deployment
SN-Get-Table-Schema	Discover config table fields	Understanding available settings

Best Practices

Start with a single knowledge base and expand sources incrementally as quality is validated
Use low temperature (0.2-0.4) for Q&A to keep responses factual and grounded
Write specific system prompts that define the assistant's role, boundaries, and response format
Enable citation display so users can verify answers against source material
Set confidence thresholds conservatively (0.65+) and adjust based on feedback
Include record context when the Q&A skill is used alongside incidents or cases
Limit conversation history to 5-7 turns to manage token usage and context relevance
Block PII in responses to prevent accidental exposure of sensitive data
Monitor feedback weekly and address patterns of negative ratings promptly
Test with real user queries from support tickets to validate response quality before launch

Troubleshooting

Issue	Cause	Resolution
Now Assist panel not visible	Panel config inactive or wrong context	Verify sn_now_assist_panel_config.active=true and context matches UI
Responses are generic/unhelpful	Knowledge sources not linked or empty	Check skill_config knowledge_base entries and verify KB has published articles
Hallucinated answers	Temperature too high or no grounding requirement	Lower temperature, set require_knowledge_grounding=true
Response cut off mid-sentence	max_tokens too low	Increase max_tokens in sn_gen_ai_config (400-600 recommended)
Slow response time	Too many knowledge sources or large context window	Reduce search sources, lower context_window_tokens
Skill not triggering	Skill status is draft or inactive	Publish and activate the skill
Feedback not collected	show_feedback disabled on panel	Set show_feedback=true in panel config
Wrong knowledge base searched	KB filter conditions too broad or missing	Add specific kb_knowledge_base filter in knowledge_filter config

Examples

Example 1: IT Agent Q&A in Workspace

Configure Now Assist Q&A for ITSM agents:

Skill: Agent workspace context, linked to IT Knowledge Base and resolved incidents
System Prompt: IT support assistant, answers from KB only, cites sources, suggests escalation paths
LLM Config: Temperature 0.3, max 400 tokens, now_llm provider
Panel: Right sidebar, auto-open disabled, feedback enabled, shows 3 source citations
Context: Include incident short_description, description, priority, category from viewed record
Guardrails: Require knowledge grounding, block PII, min confidence 0.7

Example 2: Employee Self-Service Q&A

Configure Now Assist for employee portal self-service:

Skill: Employee portal context, linked to IT FAQ KB and HR Policy KB
System Prompt: Friendly employee assistant, provides step-by-step guidance, offers catalog links
LLM Config: Temperature 0.4, max 500 tokens for more detailed self-service instructions
Panel: Embedded in portal search, greeting message, max 5 conversation turns
Fallback: If confidence below 0.6, suggest creating an incident or browsing catalog
Guardrails: Block salary/termination topics, require KB grounding, content filtering enabled

Example 3: CSM Agent Q&A for Customer Support

Configure Now Assist for customer service management agents:

Skill: Agent workspace context for CSM, linked to product KB and customer solutions KB
System Prompt: Customer support specialist, professional tone, includes troubleshooting steps
LLM Config: Temperature 0.2 for precise technical answers, max 400 tokens
Context: Include case short_description, product, account, priority from current case
Panel: Right sidebar with auto-open on case creation, feedback and sources visible
Guardrails: Prohibit sharing internal pricing, SLA details, or customer data from other accounts

Related Skills

genai/ai-search-rag - AI Search configuration that powers Q&A knowledge retrieval
genai/skill-kit-custom - Creating custom Now Assist skills beyond Q&A
genai/flow-generation - Flows that can be triggered from Q&A fallback actions
knowledge/article-generation - Managing knowledge content quality for better Q&A

About this skill

Overview

Prerequisites

Procedure

Step 1: Assess Current Now Assist Configuration

Step 2: Configure Now Assist Q&A Skill

Step 3: Configure Knowledge Sources

Step 4: Configure LLM Parameters

Step 5: Configure System Prompts

Step 6: Configure Now Assist Panel

Step 7: Configure Conversation Context

Step 8: Set Up Response Quality Guardrails

Step 9: Activate and Deploy

Step 10: Monitor and Tune Response Quality

Tool Usage

Best Practices

Troubleshooting

Examples

Example 1: IT Agent Q&A in Workspace

Example 2: Employee Self-Service Q&A

Example 3: CSM Agent Q&A for Customer Support

Related Skills