Agentforce Guardrails

Agentforce Guardrails

This skill activates when a practitioner needs to define, enforce, or troubleshoot behavioral boundaries for an Agentforce agent — covering the four-layer guardrail architecture: Topic Scope, agent-level system instructions, topic/action filters, and Instruction Adherence monitoring. It does not cover Trust Layer content filtering or general topic routing design.

Before Starting

Gather this context before working on anything in this domain:

• Confirm which Salesforce version and Agentforce tier the org is on. Guardrail features, including Instruction Adherence analytics, are generally available from Spring '25 but feature availability may vary by edition.
• Know whether the agent is internal (employee-facing) or external (customer-facing, Experience Cloud, Messaging). Customer-facing agents require stricter abuse prevention patterns because untrusted users can craft adversarial inputs.
• Know whether human escalation is required. If so, confirm that Omni-Channel is enabled and a routing configuration or flow exists — the Escalation topic is a standard system construct that only activates when Omni-Channel is properly wired. Misconfiguring or omitting Omni-Channel causes the Escalation topic to silently fail.
• Collect the current Classification Description and Scope field text for every topic. A common wrong assumption is that the Scope field drives LLM topic routing — it does not. The Classification Description field is what the LLM reads to decide which topic handles a conversation turn. The Scope field governs what actions and responses are allowed once a topic is selected.
• Note the platform limit: an agent supports up to 25 topics per agent definition (varies by Salesforce version; verify in current release notes).

Core Concepts

Guardrail Layer 1 — Topic Scope Field

The Scope field on a Bot Topic defines the behavioral boundaries that apply once the LLM has selected that topic. It tells the agent what it should do, what it should not do, and what information it is allowed to share within that topic's context. This field is enforced during the action-planning phase of the agent's reasoning loop, not during topic classification.

The Scope field is distinct from the Classification Description, which is the text the LLM reads when deciding which topic matches the current user input. Conflating these two fields is the single most common guardrail misconfiguration. A Scope field that reads "do not help with billing questions" will not prevent billing conversations from routing to this topic — only the Classification Description can do that.

Effective Scope field patterns: use declarative boundary statements ("This topic only addresses order status inquiries. It does not provide refunds or credits."). Keep the Scope under 1,500 characters. Do not repeat the Classification Description verbatim.

Guardrail Layer 2 — Agent-Level System Instructions

Agent-level system instructions apply globally across all topics and conversations. They are the correct location for:

• Default fallback behavior when no topic matches a user's input
• Prohibited subject matter that must be blocked regardless of which topic is active
• Tone and persona constraints that apply to the whole agent
• Abuse prevention language for customer-facing deployments

When no topic matches a user input, the agent uses its system instructions to determine how to respond. Without explicit fallback instructions ("If no topic matches the user's request, respond: 'I can only help with X, Y, and Z.'"), the agent may attempt to answer anyway, producing hallucinated or off-policy responses.

Overuse of imperative keywords — must, never, always, do not, you must not — causes the LLM reasoning loop to produce contradictory self-instructions and can result in the agent repeatedly re-evaluating the same turn without producing output. Use declarative boundary statements instead: "This agent addresses only [scope]. Requests outside this scope receive: '[canned response].'"

Guardrail Layer 3 — Topic Filters and Action Filters

Topic filters restrict which actions (Apex, flow, prompt templates, standard actions) are available within a specific topic. Use topic filters to ensure that an action can only be invoked in the topic context where it is safe — for example, allowing a refund flow only within a Returns topic, never in a General Inquiry topic.

Action filters apply globally to an invocable action, preventing it from being called by any topic regardless of how the agent reasons. Use action filters for actions that should be completely inaccessible to the agent (e.g., an internal admin action that is in the org's invocable action registry but must never be exposed to the agent).

Topic filters and action filters are separate configuration constructs. Both are needed in different scenarios. Action filters are the stronger control.

Guardrail Layer 4 — Instruction Adherence Monitoring

Instruction Adherence is an out-of-the-box Agentforce Analytics metric that scores how consistently the agent follows its topic instructions across conversations. A score below ~70% indicates that the instructions are ambiguous, contradictory, or too imperative in tone. Low scores are a signal to review instruction language (declarative vs. imperative), check for conflicting topic Scope statements, and look for adversarial input patterns in conversation logs.

Instruction Adherence is monitored in the Agentforce Analytics dashboard. It does not fire alerts automatically — practitioners must build monitoring habits or set up custom report subscriptions.

Escalation Topic — Standard System Construct

The Escalation topic is a system-defined topic automatically available on every Agentforce agent. Its purpose is to route a conversation to a human agent when the user requests escalation or the agent cannot resolve the request. The Escalation topic requires Omni-Channel to be enabled with a valid routing configuration or flow. Without this, the Escalation topic appears active but silently fails to route the conversation.

Practitioners cannot modify the Escalation topic's Classification Description. They can configure the routing destination (queue, flow, or skill-based routing) and add a brief customer message displayed before handoff.

Restricted Topics

Restricted topics are a guardrail configuration that prevents the agent from engaging with specific subject matter regardless of which active topic was selected. Restricted topic entries are configured at the agent level (not per topic). Examples: block all discussion of competitor pricing, legal advice, medical diagnoses.

Restricted topic entries are matched against user input before topic classification occurs, making them a pre-classification filter. A user input that matches a restricted topic entry receives a configurable refusal response and the conversation is not routed to any topic.

Common Patterns

Pattern: Layered Scope + Fallback System Instruction

When to use: Any agent where users might ask questions outside the intended topic set, especially customer-facing agents on Messaging or Experience Cloud.

How it works:

1. Write a Classification Description for each topic that tightly describes the user intent the topic handles.
2. Write a Scope field for each topic that declares what the agent will and will not do once in that topic — use declarative sentences, not imperative commands.
3. Write an agent-level system instruction that explicitly names the fallback behavior: "If the user's request does not match any available topic, respond: 'I can only assist with [list]. For other questions, please contact [channel].'"
4. Test by sending off-topic messages in the agent preview and confirming the fallback text appears verbatim.

Why not rely on topic Scope alone: Topic Scope only applies after topic selection. Without a fallback system instruction, the agent may try to answer off-topic questions using general LLM knowledge, producing policy-violating responses.

Pattern: Restricted Topic Blocklist for Customer-Facing Agents

When to use: Customer-facing agents where regulatory, legal, or brand risk requires that certain subjects are never discussed — regardless of how a user phrases the request.

How it works:

1. Navigate to Agent Setup > Restricted Topics.
2. Add one entry per prohibited subject. Write the entry as a clear subject description, not a keyword: "Competitor pricing and promotions" rather than "competitor".
3. Configure a consistent refusal response: "I'm not able to assist with that. Please contact our support team at [channel]."
4. Test with paraphrased and adversarial phrasings of the prohibited subject to confirm the restriction fires consistently.
5. Review restricted topic matches weekly in conversation logs for edge cases that bypassed the filter.

Why not use topic Scope or system instructions alone: Topic Scope and system instructions are post-classification controls. A well-phrased adversarial prompt can sometimes steer the LLM to classify into an adjacent topic. Restricted topics operate as a pre-classification, keyword-and-semantic filter, providing an additional defensive layer.

Pattern: Escalation Topic with Omni-Channel Queue Routing

When to use: Any agent that must support human handoff, including service agents on Messaging for In-App and Web or Experience Cloud.

How it works:

1. Enable Omni-Channel in the org (Setup > Omni-Channel Settings).
2. Create a queue or configure an Omni-Channel flow for the human agent pool.
3. In the agent's Escalation topic configuration, select the routing destination (queue or flow).
4. Set the pre-handoff message: "Connecting you to a support agent. Please hold."
5. Test the escalation path end-to-end in a sandbox: confirm the conversation appears in the Omni-Channel supervisor dashboard and is accepted by a human agent.

Why not skip Omni-Channel: The Escalation topic requires Omni-Channel routing infrastructure. Without it, the topic technically exists but the handoff call fails silently. The user sees the pre-handoff message but is never connected to a human agent.

Decision Guidance

Recommended Workflow

Step-by-step instructions for an AI agent or practitioner configuring or auditing Agentforce guardrails:

1. Audit current topic configuration. For each topic, read the Classification Description and Scope field separately. Confirm they serve different purposes: Classification Description drives routing, Scope drives behavioral boundaries post-selection. Flag any Scope text that attempts to block routing (it will not work).
2. Configure agent-level system instructions. Write a concise system instruction (under 2,000 characters) covering: (a) what the agent is for, (b) explicit fallback response when no topic matches, (c) tone and persona, (d) any globally prohibited responses. Use declarative language — avoid starting sentences with "you must" or "never". Example: "This agent assists employees with IT helpdesk requests. Requests outside IT support receive: 'I can only assist with IT requests. Please contact HR or Finance directly.'"
3. Configure restricted topics for prohibited subjects. Add one entry per subject that must be blocked at the pre-classification level. Write entries as subject descriptions, not raw keywords. Set a consistent refusal response text.
4. Review topic and action filters. For each action in each topic, decide: should this action be available only in this topic (topic filter) or blocked globally (action filter)? Apply the minimum necessary filter — over-filtering breaks expected agent behavior.
5. Configure the Escalation topic if human handoff is required. Verify Omni-Channel is enabled. Set routing destination (queue or flow). Test the handoff end-to-end in sandbox before deploying to production.
6. Test guardrail coverage. Send at least five off-topic, adversarial, and edge-case inputs in the agent preview. Confirm: restricted topics fire, fallback response appears for no-match scenarios, prohibited actions are not invoked, escalation routes correctly.
7. Monitor Instruction Adherence post-launch. Check the Agentforce Analytics dashboard after the first week of live traffic. If adherence is below 70%, review conversation logs for patterns — common causes are ambiguous Scope text, imperative instruction language, or user phrasings not covered by Classification Descriptions.

Review Checklist

Run through these before marking guardrail work complete:

• Every topic has a Classification Description that drives routing and a Scope field that drives post-selection behavior — they are not the same text
• Agent-level system instructions include an explicit fallback response for no-topic-match scenarios
• All prohibited subjects are added as Restricted Topic entries with a consistent refusal response
• Topic filters are configured for actions that must not cross topic boundaries
• Action filters are applied to any globally prohibited invocable actions
• Escalation topic routing destination is set and Omni-Channel configuration is verified end-to-end
• Agent-level instructions use declarative boundary language, not imperative chains (must/never/always)
• Guardrail coverage has been tested with off-topic, adversarial, and edge-case inputs in agent preview
• Instruction Adherence monitoring plan is in place (dashboard review cadence established)

Salesforce-Specific Gotchas

Non-obvious platform behaviors that cause real production problems:

1. Scope field does not control topic routing — The Scope field on a topic is read after the topic is selected. Adding "do not answer billing questions" to the Scope field of an IT Support topic does not prevent billing questions from routing there. Classification Description controls routing. This gotcha causes practitioners to write increasingly long Scope fields in an attempt to block off-topic routing, which has no effect.
2. Escalation topic silently fails without Omni-Channel — If Omni-Channel is not enabled or no routing configuration is assigned, the Escalation topic appears to activate (the user sees the pre-handoff message) but the conversation is never delivered to a human agent. There is no error surfaced to the end user. Test escalation end-to-end, not just by confirming the topic exists.
3. Imperative instruction language degrades reasoning loop reliability — Stacking must, never, always, and do not in system instructions or Scope fields can cause the LLM reasoning loop to produce contradictory internal instructions, leading to repeated self-evaluation without output (a "reasoning loop"). This appears to the user as the agent stalling or timing out. Replace with declarative statements that describe desired state.

Output Artifacts

Related Skills

• agentforce/agent-topic-design — use when the main problem is topic boundary design and routing logic rather than behavioral guardrails and abuse prevention
• agentforce/prompt-template-design — use when the issue is prompt template construction inside a topic action, not the guardrail architecture around the agent
• agentforce/agentforce-testing — use when writing test scenarios to validate agent behavior, including guardrail coverage tests