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weav.com

AI & Agents
https://weav.com/
Deliver fast, personal support with Weav’s AI customer service solutions built on your docs. Resolve tickets instantly. Don’t just deflect them.
Explore capabilities

Tools verified

page: Every page

get_pricingAnswer

Return Weav public pricing: Lite, Plus, Pro, Max monthly prices, annual discount, add-ons, and signup/sales links. Use this instead of scraping weav.com/pricing.

View tool JSON
{
  "name": "get_pricing",
  "kind": "answer",
  "impl": "imperative",
  "description": "Return Weav public pricing: Lite, Plus, Pro, Max monthly prices, annual discount, add-ons, and signup/sales links. Use this instead of scraping weav.com/pricing.",
  "inputSchema": {
    "type": "object",
    "$schema": "https://json-schema.org/draft/2020-12/schema",
    "properties": {
      "context": {
        "type": "string",
        "description": "Describe the user's underlying goal in one sentence — not the tool you're calling."
      },
      "llm_model": {
        "type": "string",
        "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
      },
      "conversation_id": {
        "type": "string",
        "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it."
      }
    },
    "required": [
      "context",
      "llm_model"
    ]
  },
  "page": "/"
}
get_product_overviewAnswer

Return a structured overview of Weav: AI agents, unified inbox, channels, training, actions, and escalation. Links to product and docs.

View tool JSON
{
  "name": "get_product_overview",
  "kind": "answer",
  "impl": "imperative",
  "description": "Return a structured overview of Weav: AI agents, unified inbox, channels, training, actions, and escalation. Links to product and docs.",
  "inputSchema": {
    "type": "object",
    "$schema": "https://json-schema.org/draft/2020-12/schema",
    "properties": {
      "context": {
        "type": "string",
        "description": "Describe the user's underlying goal in one sentence — not the tool you're calling."
      },
      "llm_model": {
        "type": "string",
        "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
      },
      "conversation_id": {
        "type": "string",
        "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it."
      }
    },
    "required": [
      "context",
      "llm_model"
    ]
  },
  "page": "/"
}
get_signupAnswer

Return the self-serve signup URL (app.weav.com/register) and what the free Lite start includes.

View tool JSON
{
  "name": "get_signup",
  "kind": "answer",
  "impl": "imperative",
  "description": "Return the self-serve signup URL (app.weav.com/register) and what the free Lite start includes.",
  "inputSchema": {
    "type": "object",
    "$schema": "https://json-schema.org/draft/2020-12/schema",
    "properties": {
      "context": {
        "type": "string",
        "description": "Describe the user's underlying goal in one sentence — not the tool you're calling."
      },
      "llm_model": {
        "type": "string",
        "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
      },
      "conversation_id": {
        "type": "string",
        "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it."
      }
    },
    "required": [
      "context",
      "llm_model"
    ]
  },
  "page": "/"
}
get_demoAnswer

Return the sales/demo booking URL (weav.com/sales). Does not collect email or other PII—return the URL for the human or agent to open.

View tool JSON
{
  "name": "get_demo",
  "kind": "answer",
  "impl": "imperative",
  "description": "Return the sales/demo booking URL (weav.com/sales). Does not collect email or other PII—return the URL for the human or agent to open.",
  "inputSchema": {
    "type": "object",
    "$schema": "https://json-schema.org/draft/2020-12/schema",
    "properties": {
      "context": {
        "type": "string",
        "description": "Describe the user's underlying goal in one sentence — not the tool you're calling."
      },
      "llm_model": {
        "type": "string",
        "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
      },
      "conversation_id": {
        "type": "string",
        "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it."
      }
    },
    "required": [
      "context",
      "llm_model"
    ]
  },
  "page": "/"
}
get_comparisonAnswer

Return a short structured contrast of Weav vs Ada, Intercom, and Zendesk, plus the comparison page URL.

View tool JSON
{
  "name": "get_comparison",
  "kind": "answer",
  "impl": "imperative",
  "description": "Return a short structured contrast of Weav vs Ada, Intercom, and Zendesk, plus the comparison page URL.",
  "inputSchema": {
    "type": "object",
    "$schema": "https://json-schema.org/draft/2020-12/schema",
    "properties": {
      "context": {
        "type": "string",
        "description": "Describe the user's underlying goal in one sentence — not the tool you're calling."
      },
      "llm_model": {
        "type": "string",
        "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
      },
      "conversation_id": {
        "type": "string",
        "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it."
      }
    },
    "required": [
      "context",
      "llm_model"
    ]
  },
  "page": "/"
}
get_more_toolsAnswer

Check for additional tools whenever your task might benefit from specialized capabilities - even if existing tools could work as a fallback.

View tool JSON
{
  "name": "get_more_tools",
  "kind": "answer",
  "impl": "imperative",
  "description": "Check for additional tools whenever your task might benefit from specialized capabilities - even if existing tools could work as a fallback.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "context": {
        "type": "string",
        "description": "A description of your goal and what kind of tool would help accomplish it."
      },
      "llm_model": {
        "type": "string",
        "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
      },
      "conversation_id": {
        "type": "string",
        "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it."
      }
    },
    "required": [
      "context",
      "llm_model"
    ]
  },
  "page": "/"
}