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fb4bac9cf0
feat: replace agentforce-development skill with three specialized skills Replace the monolithic agentforce-development skill with three focused skills: - developing-agentforce: For creating and authoring Agentforce agents - observing-agentforce: For monitoring and debugging agents - testing-agentforce: For validating agent behavior Co-authored-by: Claude Sonnet 4.5 <noreply@anthropic.com>
274 lines
8.4 KiB
Plaintext
274 lines
8.4 KiB
Plaintext
# Procedural Instructions Pattern
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# Execute actions inline within instructions block for conditional data loading
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#
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# ★ When To Use This Pattern:
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# - Fetch data only when needed (lazy loading)
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# - Chain data lookups based on conditions
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# - Build up context progressively
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# - Reduce unnecessary API calls
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#
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# ★ Key Insights:
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# - `run @actions.x` can appear INSIDE `instructions: ->` blocks
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# - Actions execute when their containing conditional is true
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# - Different from actions: block which defines what LLM CAN call
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# - This is PROCEDURAL (you control when) vs DECLARATIVE (LLM chooses)
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#
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# ★ Use Case Distinction:
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# - actions: block = "LLM, here are tools you MAY use"
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# - run in instructions = "Do this NOW when condition met"
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#
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# This is a COMPLETE template - customize for your use case
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system:
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instructions: "You are a customer service agent. Efficiently gather context as needed to help customers. Only fetch data when required for the current task."
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messages:
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welcome: "Hello! How can I help you today?"
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error: "I encountered an issue retrieving your information. Let me try again."
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config:
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agent_name: "Smart_Service_Agent"
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default_agent_user: "agent@company.salesforce.com"
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agent_label: "Smart Service Agent"
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description: "Agent with procedural data loading"
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variables:
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# Standard linked variables
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EndUserId: linked string
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source: @MessagingSession.MessagingEndUserId
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description: "Messaging End User ID"
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ContactId: linked string
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source: @MessagingEndUser.ContactId
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description: "Contact ID"
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# Progressive data loading variables
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customer_loaded: mutable boolean = False
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description: "Whether customer data has been loaded"
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orders_loaded: mutable boolean = False
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description: "Whether order data has been loaded"
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cases_loaded: mutable boolean = False
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description: "Whether case data has been loaded"
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# Customer data
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customer_name: mutable string = ""
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description: "Customer's full name"
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customer_tier: mutable string = ""
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description: "Customer tier: standard, premium, vip"
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account_id: mutable string = ""
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description: "Associated account ID"
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# Order data
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recent_order_id: mutable string = ""
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description: "Most recent order ID"
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order_status: mutable string = ""
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description: "Status of the recent order"
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tracking_number: mutable string = ""
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description: "Shipping tracking number"
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# Case data
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open_case_count: mutable number = 0
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description: "Number of open support cases"
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last_case_subject: mutable string = ""
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description: "Subject of most recent case"
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language:
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default_locale: "en_US"
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start_agent topic_selector:
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label: "Topic Selector"
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description: "Routes to topics with procedural data loading"
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actions:
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# Data loading actions
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load_customer:
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description: "Load customer profile data"
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inputs:
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contact_id: string
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description: "Contact ID to look up"
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is_required: True
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outputs:
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name: string
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description: "Customer name"
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tier: string
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description: "Customer tier"
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account_id: string
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description: "Associated account"
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target: "flow://Get_Customer_Profile"
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load_orders:
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description: "Load recent order data"
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inputs:
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contact_id: string
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description: "Contact ID"
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is_required: True
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outputs:
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order_id: string
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description: "Most recent order ID"
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status: string
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description: "Order status"
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tracking: string
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description: "Tracking number"
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target: "flow://Get_Recent_Orders"
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load_cases:
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description: "Load support case data"
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inputs:
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contact_id: string
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description: "Contact ID"
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is_required: True
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outputs:
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open_count: number
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description: "Number of open cases"
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last_subject: string
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description: "Last case subject"
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target: "flow://Get_Open_Cases"
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reasoning:
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# ★ PROCEDURAL INSTRUCTIONS with inline action execution
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instructions: ->
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# ★ STEP 1: Always load customer data first (if not already loaded)
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# This runs BEFORE any conversation happens
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if @variables.customer_loaded == False:
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run @actions.load_customer
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with contact_id=@variables.ContactId
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set @variables.customer_name = @outputs.name
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set @variables.customer_tier = @outputs.tier
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set @variables.account_id = @outputs.account_id
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set @variables.customer_loaded = True
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# Now we have customer context
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| Hello {!@variables.customer_name}!
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if @variables.customer_tier == "vip":
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| As a VIP customer, I'm here to provide priority support.
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| How can I help you today?
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| - Order status or tracking
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| - Support cases
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| - Account questions
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actions:
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go_orders: @utils.transition to @topic.order_status
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go_cases: @utils.transition to @topic.support_cases
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go_account: @utils.transition to @topic.account_help
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topic order_status:
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label: "Order Status"
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description: "Check order status with lazy loading"
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actions:
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get_tracking_details:
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description: "Get detailed tracking information"
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inputs:
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order_id: string
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description: "Order ID to look up"
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outputs:
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carrier: string
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description: "Shipping carrier"
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estimated_delivery: string
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description: "Estimated delivery date"
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current_location: string
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description: "Current package location"
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target: "flow://Get_Tracking_Details"
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reasoning:
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instructions: ->
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# ★ LAZY LOADING: Only fetch orders when user enters this topic
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if @variables.orders_loaded == False:
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run @actions.load_orders
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with contact_id=@variables.ContactId
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set @variables.recent_order_id = @outputs.order_id
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set @variables.order_status = @outputs.status
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set @variables.tracking_number = @outputs.tracking
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set @variables.orders_loaded = True
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# Now provide order information
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| Here's your most recent order:
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| Order ID: {!@variables.recent_order_id}
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| Status: {!@variables.order_status}
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if @variables.tracking_number != "":
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| Tracking: {!@variables.tracking_number}
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| Would you like more details or help with something else?
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actions:
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get_details: @actions.get_tracking_details
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with order_id=@variables.recent_order_id
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back: @utils.transition to @topic.topic_selector
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topic support_cases:
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label: "Support Cases"
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description: "Review support cases with lazy loading"
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reasoning:
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instructions: ->
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# ★ LAZY LOADING: Only fetch cases when needed
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if @variables.cases_loaded == False:
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run @actions.load_cases
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with contact_id=@variables.ContactId
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set @variables.open_case_count = @outputs.open_count
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set @variables.last_case_subject = @outputs.last_subject
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set @variables.cases_loaded = True
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# Present case information
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if @variables.open_case_count == 0:
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| You have no open support cases.
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| Is there something I can help you with?
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if @variables.open_case_count > 0:
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| You have {!@variables.open_case_count} open case(s).
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| Most recent: {!@variables.last_case_subject}
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| Would you like to:
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| - Check the status of a specific case
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| - Create a new support case
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| - Return to the main menu
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actions:
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back: @utils.transition to @topic.topic_selector
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escalate: @utils.escalate
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description: "Transfer to support specialist"
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topic account_help:
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label: "Account Help"
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description: "Account questions - customer data already loaded"
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reasoning:
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instructions: ->
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# ★ DATA ALREADY AVAILABLE - no loading needed
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# Customer data was loaded in topic_selector
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| Account Information:
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| Name: {!@variables.customer_name}
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| Tier: {!@variables.customer_tier}
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| Account ID: {!@variables.account_id}
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| What would you like to know about your account?
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actions:
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back: @utils.transition to @topic.topic_selector
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# ★ Insight: Procedural vs Declarative Actions
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#
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# PROCEDURAL (run in instructions):
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# - You control WHEN the action runs
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# - Executes based on conditionals
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# - Good for: data loading, setup, guaranteed actions
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# - Example: "Always load customer before greeting"
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#
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# DECLARATIVE (actions: block):
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# - LLM decides IF and WHEN to call
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# - Based on user request
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# - Good for: optional tools, user-triggered actions
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# - Example: "User can ask for refund if they want"
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#
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# COMBINE BOTH:
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# - Use procedural for setup/loading
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# - Use declarative for user interactions
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# - Result: Efficient, context-aware agents
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# ★ Performance Benefits:
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# - Fetch only what's needed per topic
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# - Avoid loading all data upfront
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# - Reduce API calls for simple conversations
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# - Better response times
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