AI-Studio/documentation/Tools.md

Tool Development

This document explains how model-driven tools are added to AI Studio. Tool calling let a model request a small, well-defined action during a chat or assistant run, such as searching the web or reading a web page.

Tools are part of the .NET app. They are not Lua plugins and they are not loaded dynamically from user folders. Adding a tool requires code changes.

Architecture

A tool has two parts:

• A JSON definition in app/MindWork AI Studio/wwwroot/tool_definitions/
• A C# implementation of IToolImplementation in app/MindWork AI Studio/Tools/ToolCallingSystem/ToolCallingImplementations/

At startup, ToolRegistry reads all JSON definitions and matches each definition to a registered implementation by implementationKey. ToolExecutor runs the implementation when a provider returns a matching function call.

The provider only sees tools that are available for the current component, selected by the user or defaults, supported by the model, configured correctly, and allowed by the provider confidence rules.

Definition File

Create one JSON file per tool under wwwroot/tool_definitions. The file describes the user-visible tool metadata, optional settings, and the function schema sent to the model.

Example:

{
  "schemaVersion": 1,
  "id": "get_current_weather",
  "implementationKey": "get_current_weather",
  "visibleIn": {
    "chat": true,
    "assistants": true
  },
  "settingsSchema": {
    "type": "object",
    "properties": {
      "demoLabel": {
        "type": "string",
        "secret": false
      }
    },
    "required": [
      "demoLabel"
    ]
  },
  "function": {
    "name": "get_current_weather",
    "description": "Get the current weather in a given location.",
    "strict": true,
    "parameters": {
      "type": "object",
      "properties": {
        "city": {
          "type": "string",
          "description": "The city to find the weather for, e.g. 'San Francisco'."
        },
        "state": {
          "type": "string",
          "description": "The two-letter abbreviation for the state, e.g. 'CA'."
        },
        "unit": {
          "type": "string",
          "description": "The unit to fetch the temperature in.",
          "enum": [
            "celsius",
            "fahrenheit"
          ]
        }
      },
      "required": [
        "city",
        "state",
        "unit"
      ],
      "additionalProperties": false
    }
  }
}

Use stable lower-case IDs with underscores. Keep id, implementationKey, and function.name identical unless there is a clear compatibility reason not to.

Implementation

Implement IToolImplementation and register the class in Program.cs as an IToolImplementation.

Example:

using System.Text.Json;
using AIStudio.Tools.PluginSystem;

namespace AIStudio.Tools.ToolCallingSystem.ToolCallingImplementations;

public sealed class GetCurrentWeatherTool : IToolImplementation
{
    private static string TB(string fallbackEN) => I18N.I.T(fallbackEN, typeof(GetCurrentWeatherTool).Namespace, nameof(GetCurrentWeatherTool));

    public string ImplementationKey => "get_current_weather";

    public string Icon => Icons.Material.Filled.Cloud;

    public IReadOnlySet<string> SensitiveTraceArgumentNames => new HashSet<string>(StringComparer.Ordinal);

    public string GetDisplayName() => TB("Current Weather");

    public string GetDescription() => TB("Use this demo tool to retrieve the current weather for a given city and state.");

    public string GetSettingsFieldLabel(string fieldName, ToolSettingsFieldDefinition fieldDefinition) => fieldName switch
    {
        "demoLabel" => TB("Demo Label"),
        _ => TB(fieldDefinition.Title),
    };

    public string GetSettingsFieldDescription(string fieldName, ToolSettingsFieldDefinition fieldDefinition) => fieldName switch
    {
        "demoLabel" => TB("Required demo setting for validating tool settings."),
        _ => TB(fieldDefinition.Description),
    };

    public Task<ToolExecutionResult> ExecuteAsync(JsonElement arguments, ToolExecutionContext context, CancellationToken token = default)
    {
        var city = arguments.TryGetProperty("city", out var cityValue) ? cityValue.GetString() ?? string.Empty : string.Empty;
        var state = arguments.TryGetProperty("state", out var stateValue) ? stateValue.GetString() ?? string.Empty : string.Empty;
        var unit = arguments.TryGetProperty("unit", out var unitValue) ? unitValue.GetString() ?? string.Empty : string.Empty;

        if (unit is not ("celsius" or "fahrenheit"))
            throw new ArgumentException($"Invalid unit '{unit}'.");

        return Task.FromResult(new ToolExecutionResult
        {
            TextContent = $"The weather in {city}, {state} is 85 degrees {unit}.",
        });
    }
}

Register it:

builder.Services.AddSingleton<IToolImplementation, GetCurrentWeatherTool>();

The example above is documentation-only. Do not keep demo tools in the production tool catalog.

Settings And Secrets

Tool settings are stored through ToolSettingsService. Plain settings are stored in the regular configuration data. Settings marked with "secret": true are stored in the OS keyring through the Rust service.

Use ValidateConfigurationAsync when a setting needs more than "required field is present" validation, such as URL syntax, numeric limits, mutually exclusive options, or allowlist parsing.

Use SensitiveTraceArgumentNames for model-provided arguments that must not be shown in tool traces. Do not return secrets in TextContent, JsonContent, exception messages, logs, or trace formatting.

Security

Treat model-provided tool arguments as untrusted input.

For tools that perform network requests:

• Accept only the schemes and hosts that are required for the feature.
• Validate redirects before following them.
• Do not allow model-supplied URLs to access localhost, loopback, link-local, multicast, or private network targets unless the feature has an explicit policy for that.
• Check ToolExecutionContext.ProviderConfidence before returning sensitive data to the model.
• Throw ToolExecutionBlockedException for intentional policy blocks so the UI can show the call as blocked instead of failed.

For settings that administrators should be able to manage centrally, add the setting to the appropriate Settings/DataModel class, register it with ManagedConfiguration.Register(...), process it in PluginConfiguration, clean leftovers in PluginFactory.Loading, and document it in Plugins/configuration/plugin.lua.

Checklist

• Add the JSON definition in wwwroot/tool_definitions.
• Add the IToolImplementation class.
• Register the implementation in Program.cs.
• Validate settings and model arguments.
• Protect secrets and sensitive trace arguments.
• Add provider-confidence checks when tool output may contain sensitive data.
• Update configuration plugin documentation when admins can manage the setting.
• Add a changelog entry when users or administrators are affected.