Docs/Guides/Agent Capabilities

    Message Tagging

    Last updated · MAR 2026·Read as Markdown

    Message tags are one of the most useful features in AVCodex. They let you automatically detect specific kinds of messages and take action: route a frustrated client to a human, flag a warranty escalation, block off-topic requests, or track project leads coming in through a public-facing agent.

    A few common patterns:

    • Route a tech who needs a senior engineer to a human dispatcher.
    • Detect "this is broken right now" so a service desk agent can flag emergencies.
    • Catch warranty and RMA requests for the parts team.
    • Block off-topic chatter on a public room support agent.
    • Track design and pricing intent on a pre-sales agent that handles RFP questions.

    Unlike keyword matching, AVCodex uses semantic similarity to understand the meaning behind messages. That means your tags catch variations and paraphrases you never explicitly defined.

    Why semantic matching matters#

    Keyword systems force you to anticipate every phrasing. Semantic matching does not.

    • "I want to talk to a human" matches "Can I speak with a real person?"
    • "What's the price?" matches "How much does this DSP cost?"
    • "I'm frustrated" matches "This room is down again and I'm losing my mind."

    You define a few example phrases. The AI handles the underlying intent.

    Set up your first tag by following the step-by-step in the dashboard.

    Each tag has several settings.

    Tag name#

    Give your tag a clear, descriptive name. You will see this in analytics and chat history, so make it readable at a glance.

    Good names: "Human Escalation", "Pricing Question", "Warranty Claim", "Emergency Service".

    Bad names: "Tag 1", "Important", "Check".

    Example phrases#

    Add 3 to 5 phrases that represent the type of message you want to detect. The AI uses these to learn the meaning, so favor variety.

    code
    Good examples for "Human Needed":
- "I need to talk to a human"
- "Can I speak with a real person?"
- "Connect me to dispatch"
- "I want to talk to someone now"

Less effective (too similar):
- "Talk to human"
- "Speak to human"
- "Human please"
- "Get me a human"

    Detection sensitivity#

    The sensitivity slider controls how closely a message must match your examples to fire the tag.

    Sensitivity Best for Trade-off
    Low (50 to 65%) Catching every variation More false positives
    Medium (70 to 80%) Balanced detection Good starting point
    High (85 to 95%) Precise matching only May miss variations

    Tip: Start at 75% and tune based on what you see in chat history.

    Blocking response (optional)#

    For safety or compliance tags, you can replace the AI's response entirely when a tag fires. Useful for:

    • Off-topic requests: redirect to your agent's purpose (your room support agent should not be answering political questions).
    • Sensitive topics: provide specific guidance or a disclaimer.
    • Hard handoffs: "I'm escalating this to dispatch right now. Please stay on the line."

    When you add a blocking response, the AI does not generate anything. Your exact text shows instead.

    Start small#

    Begin with 2 to 3 high-value tags rather than covering every scenario. Add more as you learn what your users are asking.

    Review matches regularly#

    Check tag matches in chat history to spot false positives and missed detections. That feedback helps you tune sensitivity and add better example phrases.

    Use specific examples#

    The more specific and varied your example phrases, the better the detection. Generic phrases bring in noise.

    Do not over-block#

    Use blocking responses only when needed. For most tags, let the AI respond naturally while you track the conversation in the background.

    A few setups to get started.

    Service desk agent#

    Tag Purpose Blocking?
    Human Needed Route frustrated callers to dispatch. No
    Warranty Claim Flag for the parts team. No
    Emergency Service Surface a hard-down room or event. No

    Pre-sales / RFP assistant#

    Tag Purpose Blocking?
    Purchase Intent Identify hot leads on a 20-room refresh. No
    Pricing Question Track interest in specific manufacturer SKUs. No
    Competitor Mention Monitor positioning vs other integrators. No

    Public room support agent#

    Tag Purpose Blocking?
    Off-Topic Redirect non-AV chatter back to room support. Yes
    Complex Question Flag a senior engineer follow-up. No
    Feedback Collect suggestions from end users. No

    Once tags are live, you can see them at work:

    1. Chat History: each message shows any tags that fired.
    2. Tag Detail View: click a tag to see every match, sorted by recency.
    3. Remove false positives: click the X on any incorrectly tagged message to improve future detection.

    Combine with Custom Actions#

    Use tags as triggers for more complex workflows. When a tag fires, you can:

    • Send a Slack notification to dispatch.
    • Create a ticket in your service CRM.
    • Update a spreadsheet.
    • Trigger an email to the project manager.

    Multiple tags per message#

    One message can fire multiple tags. "I need a quote for replacement DSPs and I want to speak to someone today" might fire both "Pricing Question" and "Human Needed."

    Tag categories#

    Organize related tags with consistent naming prefixes:

    • Service: Human Needed
    • Service: Warranty Claim
    • Sales: Pricing Question
    • Sales: Demo Request

    Tags are not detecting anything#

    • Lower the sensitivity threshold.
    • Add more varied example phrases.
    • Check that the tag is enabled.

    Too many false positives#

    • Raise the sensitivity threshold.
    • Tighten example phrases.
    • Drop overly generic examples.

    Tags detecting the wrong things#

    • Review example phrases for unintended patterns.
    • Add negative examples (phrases that should not match).
    • Split into more specific tags.

    Now that you know how tagging works, set up your first tag:

    1. Think about what user messages you most want to detect.
    2. Create a tag with 3 to 5 good example phrases.
    3. Start at 75% sensitivity.
    4. Monitor chat history for a few days.
    5. Tune based on what you see.

    Tags get more valuable over time as you refine them on real conversations. Start simple, iterate often, and you build a powerful automation layer on top of your AVCodex agent.

    You can manage tags through code using the AVCodex MCP Server, including AI-powered utterance generation.

    Available tools#

    Tool Description
    list_tags List all tags for an agent.
    create_tag Create a new tag with utterances and actions.
    update_tag Update tag name, utterances, or actions.
    delete_tag Remove a tag.
    list_tag_instances View messages that matched a tag.
    remove_tag_instance Remove a false positive match.
    generate_utterances AI-generate training phrases for a tag.

    Example prompts#

    code
    "Create a tag called 'pricing_intent' for my pre-sales agent"
"Generate 200 utterances for detecting warranty escalations"
"Show messages that matched the 'human_needed' tag"
"Remove the false positive from tag instance xyz"

    Workflow: AI-powered tag training#

    code
    You: Create a tag for detecting pricing questions in my pre-sales agent.

AI: [Calls create_tag]
Created tag "pricing_intent". Want me to generate training utterances?

You: Yes, generate 200 varied examples for AV integration pricing.

AI: [Calls generate_utterances with count=200, domain="AV integration"]
Generated 200 utterances including:
- "What's the install cost for a 12-room refresh?"
- "How much would a Q-SYS Core 510i system run?"
- "Do you offer volume pricing on Crestron DM-NVX?"
- "Is there a service contract option?"
...

Saved to tag "pricing_intent". The tag is now active.
    Note: MCP server access requires a Builder plan or higher. See the MCP Setup Guide to get started.

    *AVCodex · Your AV expertise. Amplified by AI.*

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