Tool Selection

Documentation Index

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Why use Tool Selection?

• Enforcing a contract between the client (declared tools) and the model (tool calls)
• Reducing runtime errors by validating tool-call arguments against schemas
• Providing an optional semantic guardrail to detect risky or incorrect tool invocations even when arguments look syntactically valid
• Offering explicit, actionable feedback (allow vs. block) before tools are actually executed

• Multi-tool agents with critical or expensive tools (payment, DB write, infra actions)
• Tiered access where only some users/tenants can use certain tools
• Strict safety posture requiring both schema and semantic validation

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What it does

• Parses the request to collect the list of declared tools (names and optional schemas)
• Parses the model response to extract tool calls
• Validates each tool call:
  • Is the tool in the declared tools list?
  • If a JSON schema is provided for the tool, do the arguments conform?
  • Optional semantic validation via LLM (OpenAI) to catch risky or incorrect tool calls
• Actions:
  • Allow when all validations pass
  • Block with an error (HTTP 403) if a tool call is not declared, violates schema, or fails semantic validation
• Stage: PreResponse

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Validation flow (step‑by‑step)

1. Extract declared tools (from the client request):

• Names are required; schemas are optional but recommended

2. Extract tool calls (from the model response):

• Includes tool name and arguments

3. Structural checks:

• Tool must exist in the declared tools list
• If a schema is present for that tool, arguments must validate against the schema

4. Optional semantic check (if openai_api_key set):

• Uses OpenAI to reason about the suitability of the tool call given the request context and model reasoning summary
• Returns a compact allow/deny decision with a short rationale

5. Decision:

• If any check fails → block with HTTP 403 (and include diagnostics in telemetry)
• Otherwise → allow the response to proceed

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Configuration Parameters

• Stage: PreResponse
• If parsing fails or there are no tools/tool calls, the request is allowed
• Schema validation runs when schemas are provided in the request tool definitions
• Semantic validation runs only when openai_api_key is configured

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Prerequisites

{
  "name": "{{upstream_service_name}}",
  "algorithm": "round-robin",
  "targets": [
    {
      "provider": "openai",
      "provider_options": { "api": "responses" },
      "weight": 50,
      "priority": 1,
      "default_model": "gpt-4o-mini",
      "models": ["gpt-4", "gpt-4o-mini"],
      "stream": false,
      "credentials": { "api_key": "" }
    }
  ]
}

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Example configuration

{
  "name": "tool_selection",
  "enabled": true,
  "stage": "pre_response",
  "priority": 1,
  "parallel": false,
  "settings": {
    "openai_api_key": "${OPENAI_API_KEY}",
    "model": "gpt-4o-mini"
  }
}

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Request and response examples

{
  "messages": [
    { "role": "user", "content": "Book a meeting for tomorrow at 3pm with Alice." }
  ],
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "create_calendar_event",
        "description": "Create a calendar event",
        "parameters": {
          "type": "object",
          "properties": {
            "title": { "type": "string" },
            "datetime": { "type": "string", "format": "date-time" },
            "attendees": { "type": "array", "items": { "type": "string" } }
          },
          "required": ["title", "datetime"]
        }
      }
    }
  ]
}

{
  "tool_calls": [
    {
      "name": "create_calendar_event",
      "arguments": {
        "title": "Meeting with Alice",
        "datetime": "2025-11-14T15:00:00Z",
        "attendees": ["[email protected]"]
      }
    }
  ],
  "reasoning_summary": "User asked to book a meeting for tomorrow at 3pm."
}

• If the tool is undeclared → block
• If required fields missing or invalid schema → block
• If semantic validator denies (e.g., risky context) → block
• Otherwise → allow

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Compatibility

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Best practices

• Always declare tool schemas in the client request to enable strict validation
• Start without semantic validation to establish baseline; then enable with an appropriate model
• Combine with Tool Permission (allow/deny) and Tool Budget Limiter for layered agent security