Tools extend what your AI agent can do beyond answering questions. With tools, your agent can:
Fetch data from external APIs (product info, order status, weather)Display rich content (product cards, carousels, tables)Collect information through interactive formsTrigger actions in your systems (create tickets, send notifications)
Ansa supports three types of tool execution:
Type Description Use Case httpMakes HTTP requests to APIs Fetch data, trigger webhooks formDisplays interactive forms Collect user information mockReturns static/templated responses Testing, demos
Navigate to Agent → Tools → Create Tool :
Basic Configuration Every tool needs:
Field Description Example Name Unique identifier (lowercase, underscores) search_productsDescription When should the AI use this tool? ”Search for products when user asks about items” Input Schema Parameters the tool accepts See below
Naming Conventions Tool names must:
Start with a letter or underscore
Use only lowercase letters, numbers, and underscores
Be unique within the agent
Pattern: /^[a-z_][a-z0-9_]*$/
✅ search_products, get_order_status, contact_form
❌ Search Products, get-order, 123tool
Define what parameters the AI should provide:
{ "type" : "object" , "properties" : { "query" : { "type" : "string" , "description" : "The search term to look for" }, "category" : { "type" : "string" , "description" : "Product category to filter by" , "enum" : [ "electronics" , "clothing" , "home" ] }, "limit" : { "type" : "number" , "description" : "Maximum number of results" } }, "required" : [ "query" ] }
Write clear descriptions for each property. The AI uses these to understand what values to provide.
When a user sends a message, the AI:
Analyzes the user’s requestDecides if a tool would help answer itExtracts the required parameters from the conversationCalls the tool with those parametersProcesses the result and responds naturally
The AI decides to use a tool based on the tool’s description . Write descriptions that clearly explain when the tool should be used:
Good descriptions:
“Search for products when the user asks about items, prices, or availability”
“Look up order status when user provides an order number or asks about shipping”
“Show the contact form when user wants to reach support or has an issue you cannot resolve”
Poor descriptions:
“Product search” (too vague)
“Use this tool” (no context)
LLM Provider Differences Different AI providers handle tool calling differently:
These providers have built-in support for tools:
Provider Models Reliability Anthropic Claude 3.5 Sonnet, Claude 3 Opus Excellent OpenAI GPT-4o, GPT-4 Turbo, GPT-3.5 Turbo Excellent Google Gemini Pro, Gemini Ultra Good
Text-Based Fallback (Ollama) Local models via Ollama don’t have native tool calling. Ansa uses a text-based fallback:
Tool definitions are injected into the system prompt
The model is instructed to output JSON when using tools:
{ "tool" : "tool_name" , "arguments" : { "param" : "value" }}
Ansa parses the JSON from the response
Text-based tool calling is less reliable than native support. For complex tool use, prefer Claude or GPT models. Ollama works best for simple tools or when privacy is the priority.
Model Recommendations by Use Case Use Case Recommended Model Why Complex tools Claude 3.5 Sonnet Best at multi-step tool use E-commerce GPT-4o Fast, accurate product handling Simple lookups GPT-4o-mini Cost-effective Privacy-critical Ollama (Llama 3.2) Local, no data leaves server
User Message ↓ AI analyzes request ↓ AI decides to use tool ↓ Ansa executes tool ├── HTTP: Makes API request ├── Form: Returns schema to widget └── Mock: Returns templated response ↓ Result returned to AI ↓ AI generates natural response ↓ Response + rich display sent to user
Toggle tools on/off without deleting them:
Enabled — AI can use this toolDisabled — Tool is hidden from AI
Useful for:
Seasonal tools (holiday promotions)
A/B testing different tools
Temporarily disabling broken integrations
Organize your tools by purpose:
Category Examples Data Lookup Product search, order status, user info Forms Contact, lead capture, surveys Actions Create ticket, send notification Display Show pricing table, feature comparison
Next Steps
HTTP Tools Connect to external APIs
Form Tools Collect user information
Display Configuration Show rich content
Marketplace Install pre-built tools
See Also 
