The behavior of gemma4-it:e4b running in FastFlowLM and llama.cpp is very different: the model running in FFLM does not use the appropriate tools

[antrv]

I'm running FLM serve command on laptop with Windows 11 x64 and Ryzen AI 7 360 Pro.

flm serve gemma4-it:e4b -p 1234 --ctx-len 65536 --q-len 20 --socket 20 --cors 0

I run a simple C# console application which uses OpenAI API and define tools like get_time, list_directory, read_file, write_file, edit_file as well as system prompt to use skills in .skills subdirectory. I have .skills/task-manager/SKILL.md file with the description of the skill to manage TODO list in tasks.md file.

I enter the following user prompt: I need to buy bread, eggs and milk. Add the task to the todo list.

The behavior with FLM:

You: I need to buy bread, eggs and milk. Add the task to the todo list

Model: I can certainly help you manage your tasks, but I do not have a built-in "todo list" tool or file system access to maintain one unless you specify where it should be saved.

If you would like me to add this task to a specific file (e.g., `todo.txt`), please let me know the path, and I can use the `write_file` tool for you!

The behavior with llama.cpp (the command is .\llama-server -hf ggml-org/gemma-4-E4B-it-GGUF --jinja -c 0 --host 127.0.0.1 --port 1234):

You: I need to buy bread, eggs and milk. Add the task to the todo list

  → list_directory({"path":".skills"})
  ← {
  "directory": ".skills",
  "subdirectories": [
    "task-manager"
  ],
  "files": [],
  "message": "If you don\u0027t see the file you need, check subdirectories."
}

  → read_file({"path":".skills/task-manager/SKILL.md"})
  ← **SKILL.md content**

  → read_file({"path":"tasks.md"})
  ← { "error": "File not found: tasks.md" }

  → write_file({"content":"# My Tasks\n- [ ] Buy bread, eggs and milk","path":"tasks.md"})
  ← { "status": "success", "message": "File saved to tasks.md." }

Model: I have added "Buy bread, eggs and milk" to your todo list in `tasks.md`.

.skills/task-manager/SKILL.md file:

---
name: task-manager
description: Manages a daily todo list, adding new tasks or marking existing ones as complete with a timestamp.
---

# Task Manager Skill

You are responsible for managing the user's task list located at `tasks.md`.

## Workflow: Marking a Task as Complete
If the user asks to complete, finish, or check off a task, follow these EXACT steps:

1. **Get Context**: Call `read_file(path="tasks.md")` to see the current tasks.
   * *Fallback*: If the file does not exist, tell the user there are no tasks to complete.
2. **Get Time**: Call `get_time()` so you know when this task was completed.
3. **Execute Update**: Call `edit_file` to update the task.
   * `search_text`: The exact line of the uncompleted task (e.g., `- [ ] Fix the C++ memory leak`)
   * `replacement_text`: The same line, but with an `x` and the current date/time appended (e.g., `- [x] Fix the C++ memory leak (Completed: Thursday, October 26)`)

## Workflow: Adding a New Task
If the user asks to add a new task, follow these EXACT steps:

1. **Check State**: Call `read_file(path="tasks.md")` to see the current file.
2. **Create if Missing**: If the file does not exist, use `write_file` to create `tasks.md` with the content:
   # My Tasks
   - [ ] New Task Name
3. **Append if Exists**: If the file *does* exist, use `edit_file` to add the task. 
   * *Hint for Appending*: Find the last task in the list to use as your `search_text`. 
   * `replacement_text`: The last task, followed by a newline `\n`, followed by the new task `- [ ] Your new task`.

## Constraints
- ALWAYS use `read_file` before `edit_file` so you know the exact `search_text` to use.
- Do not make up tasks; only use what the user provided.

C# source code (.NET 10):

using Microsoft.Extensions.Logging;
using System.ClientModel;
using System.ClientModel.Primitives;
using System.Reflection;
using System.Text.Json;
using OpenAI;
using OpenAI.Chat;
using OpenAI.Models;

#pragma warning disable OPENAI001

Init.LoggingOptions.EnableLogging = true;
Init.LoggingOptions.EnableMessageLogging = true;
Init.LoggingOptions.EnableMessageContentLogging = false;

OpenAIClient client = Init.CreateClient();
List<string> models = await Init.GetAvailableModels(client);
if (models.Count == 0)
{
    Console.WriteLine("No models found.");
    return;
}

Init.PrintModels(models);
string model = "gemma4-it:e4b"; //models[0];
Console.WriteLine($"Using model: {model}");

ChatClient chatClient = client.GetChatClient(model);
ChatCompletionOptions options = new()
{
    Temperature = 0.1f, // Reduced for tool use consistency; 0.8 is often too "creative" for JSON tool calling
    Tools =
    {
        ChatTool.CreateFunctionTool(
            functionName: "get_time",
            functionDescription: "Returns the current time. Use this when the user's request is time-sensitive or relates to scheduling."),

        ChatTool.CreateFunctionTool(
            functionName: "list_directory",
            functionDescription: "Lists files/folders. REQUIRED for 'Skill Discovery': check the '.skills' folder to see what specialized skills are available.",
            functionParameters: BinaryData.FromString("""
            {
                "type": "object",
                "properties": {
                    "path": { "type": "string", "description": "Path to list (e.g. '.skills' or './project')" }
                },
                "required": ["path"]
            }
            """)),

        ChatTool.CreateFunctionTool(
            functionName: "read_file",
            functionDescription: "Reads file content. REQUIRED for 'Skill Activation': read the '.skills/<name>/SKILL.md' file to learn how to perform a specific task.",
            functionParameters: BinaryData.FromString("""
            {
                "type": "object",
                "properties": {
                    "path": { "type": "string", "description": "Relative path to the file." }
                },
                "required": ["path"]
            }
            """)),

        ChatTool.CreateFunctionTool(
            functionName: "write_file",
            functionDescription: "Creates a new file or overwrites an existing one with new content.",
            functionParameters: BinaryData.FromString("""
            {
                "type": "object",
                "properties": {
                    "path": { "type": "string", "description": "Path where the file should be saved." },
                    "content": { "type": "string", "description": "The full text content to write." }
                },
                "required": ["path", "content"]
            }
            """)),

        // Search and Replace pattern is easier for 4B models than line numbers
        ChatTool.CreateFunctionTool(
            functionName: "edit_file",
            functionDescription: "Updates a specific section of a file using a search-and-replace pattern.",
            functionParameters: BinaryData.FromString("""
            {
                "type": "object",
                "properties": {
                    "path": { "type": "string", "description": "Path to the file to edit." },
                    "search_text": { "type": "string", "description": "The exact string currently in the file that needs to change." },
                    "replacement_text": { "type": "string", "description": "The new text to put in place of the search_text." }
                },
                "required": ["path", "search_text", "replacement_text"]
            }
            """))
    },
};

const string systemPrompt =
    """
    # Role and Environment
    You are an autonomous AI orchestration agent running in a local environment. 
    Your primary function is to fulfill user requests by effectively using your available tools and 
    discovering specialized workflows called "Skills."
    
    # Available Tools & Their Usage
    You have access to the following tools. Never hallucinate tools outside of this list.
    - `get_time`: Use this if the user asks for the current date/time, or if a task requires scheduling context.
    - `list_directory`: Use this to explore folders. **CRITICAL:** Use this on the `.skills` directory if you need to discover available specialized workflows.
    - `read_file`: Use this to read file contents. **CRITICAL:** Use this to read `.skills/<skill_name>/SKILL.md` files to learn how to execute a specific skill.
    - `write_file`: Use this to create entirely new files or completely overwrite existing ones.
    - `edit_file`: Use this to modify a specific section of an existing file using a search-and-replace text match. 
    
    # The "Skill Discovery" Workflow (Progressive Disclosure)
    You do not know everything upfront. If the user asks for a complex task, a specific company workflow, or a specialized process, you MUST follow this sequence:
    1. **Discover:** Call `list_directory` on the path `.skills`. 
    2. **Identify:** Look at the returned folder names. Choose the one that best matches the user's request.
    3. **Learn:** Call `read_file` on `.skills/<chosen_folder>/SKILL.md`.
    4. **Execute:** Read the instructions provided in the `SKILL.md` file and use your file t
    """;

List<ChatMessage> history =
[
    new SystemChatMessage(systemPrompt),
];

Console.WriteLine("Chat with the model.");
Console.WriteLine("Print 'exit' to exit.\n");
while (true)
{
    Console.ForegroundColor = ConsoleColor.DarkCyan;
    Console.Write("You: ");
    string? input = Console.ReadLine()?.Trim();
    Console.ResetColor();
    if (string.IsNullOrWhiteSpace(input))
        continue;

    if (input == "exit")
    {
        Console.WriteLine("Bye!");
        break;
    }

    history.Add(new UserChatMessage(input));

    while (true)
    {
        ClientResult<ChatCompletion> response = await chatClient.CompleteChatAsync(history, options);
        ChatCompletion message = response.Value;
        history.Add(new AssistantChatMessage(message));

        if (message.FinishReason == ChatFinishReason.ToolCalls)
        {
            foreach (ChatToolCall? call in message.ToolCalls)
            {
                Console.ForegroundColor = ConsoleColor.Yellow;
                Console.WriteLine($"  → {call.FunctionName}({call.FunctionArguments})");
                Console.ResetColor();

                string result = DispatchTool(call.FunctionName, call.FunctionArguments.ToString());

                Console.ForegroundColor = ConsoleColor.DarkGray;
                Console.WriteLine($"  ← {result[..Math.Min(300, result.Length)]}");
                Console.ResetColor();

                history.Add(new ToolChatMessage(call.Id, result));
            }

            continue;
        }

        Console.ForegroundColor = ConsoleColor.Green;

        foreach (ChatMessageContentPart contentPart in message.Content)
            Console.WriteLine($"Model: {contentPart.Text}\n");

        Console.ResetColor();

        Console.WriteLine($"Input token count: {message.Usage.InputTokenCount}, " +
            $"output token count: {message.Usage.OutputTokenCount}");

        break;
    }
}

static string DispatchTool(string name, string argsJson)
{
    try
    {
        // Some local models wrap JSON in extra braces or markdown blocks
        argsJson = argsJson.Trim().Trim('`').Replace("json", "");
        if (argsJson.StartsWith("{{") && argsJson.EndsWith("}}"))
        {
            argsJson = argsJson.Substring(1, argsJson.Length - 2);
        }

        using JsonDocument doc = JsonDocument.Parse(argsJson);
        JsonElement args = doc.RootElement;

        return name switch
        {
            "get_time" => GetTime(),
            "list_directory" => Listing(args.GetProperty("path").GetString()!),
            "read_file" => ReadFile(args.GetProperty("path").GetString()!),
            "write_file" => WriteFile(args.GetProperty("path").GetString()!, args.GetProperty("content").GetString()!),
            "edit_file" => EditFile(
                args.GetProperty("path").GetString()!,
                args.GetProperty("search_text").GetString()!,
                args.GetProperty("replacement_text").GetString()!),
            _ => $"{{ \"error\": \"Unknown tool: {name}\" }}"
        };
    }
    catch (Exception ex)
    {
        return $"{{ \"error\": \"Exception using tool {name}: {ex.Message}\" }}";
    }
}

// Ensures the requested path is inside the BasePath to prevent directory traversal.
static string GetValidatedPath(string inputPath)
{
    string basePath = Utils.GetWorkspacePath();

    string fullPath = Path.GetFullPath(Path.Combine(basePath, inputPath));

    if (!fullPath.StartsWith(basePath, StringComparison.OrdinalIgnoreCase))
    {
        throw new UnauthorizedAccessException(
            "Access Denied: You cannot access files outside of the workspace directory.");
    }

    return fullPath;
}

static string GetTime()
{
    DateTime now = DateTime.Now;
    return $"{{ \"current_date\": \"{now:D}\", \"current_time\": \"{now:T}\", \"timezone\": \"{TimeZoneInfo.Local.DisplayName}\" }}";
}

static string Listing(string path)
{
    try
    {
        string targetPath = GetValidatedPath(path);
        if (!Directory.Exists(targetPath))
            return $"{{ \"error\": \"Directory not found: {path}\" }}";

        // Get relative paths to keep the model's context clean
        IEnumerable<string> dirs = Directory.EnumerateDirectories(targetPath).
            Select(p => Path.GetRelativePath(targetPath, p));

        IEnumerable<string> files = Directory.EnumerateFiles(targetPath).
            Select(p => Path.GetRelativePath(targetPath, p));

        return JsonSerializer.Serialize(new
        {
            directory = path,
            subdirectories = dirs,
            files = files,
            message = "If you don't see the file you need, check subdirectories.",
        }, new JsonSerializerOptions { WriteIndented = true });
    }
    catch (Exception ex)
    {
        return $"{{ \"error\": \"{ex.Message}\" }}";
    }
}

static string ReadFile(string path)
{
    try
    {
        string targetPath = GetValidatedPath(path);
        return File.Exists(targetPath)
            ? File.ReadAllText(targetPath)
            : $"{{ \"error\": \"File not found: {path}\" }}";
    }
    catch (Exception ex)
    {
        return $"{{ \"error\": \"{ex.Message}\" }}";
    }
}

static string WriteFile(string path, string content)
{
    try
    {
        string targetPath = GetValidatedPath(path);

        string? directory = Path.GetDirectoryName(targetPath);
        if (directory != null && !Directory.Exists(directory))
            Directory.CreateDirectory(directory);

        File.WriteAllText(targetPath, content);
        return $"{{ \"status\": \"success\", \"message\": \"File saved to {path}.\" }}";
    }
    catch (Exception ex)
    {
        return $"{{ \"error\": \"{ex.Message}\" }}";
    }
}

static string EditFile(string path, string searchText, string replacementText)
{
    try
    {
        string targetPath = GetValidatedPath(path);
        if (!File.Exists(targetPath))
            return $"{{ \"error\": \"File not found: {path}\" }}";

        string content = File.ReadAllText(targetPath);

        if (!content.Contains(searchText))
        {
            return
                $"{{ \"error\": \"The exact search_text was not found in {path}. Use 'read_file' to confirm the exact content before editing.\" }}";
        }

        string newContent = content.Replace(searchText, replacementText);
        File.WriteAllText(targetPath, newContent);

        return $"{{ \"status\": \"success\", \"message\": \"Successfully replaced text in {path}.\" }}";
    }
    catch (Exception ex)
    {
        return $"{{ \"error\": \"{ex.Message}\" }}";
    }
}

public static class Init
{
    public static readonly ClientLoggingOptions LoggingOptions = new()
    {
        EnableLogging = true,
        LoggerFactory = new MyLoggerFactory(),
        EnableMessageContentLogging = true,
        EnableMessageLogging = true,
        MessageContentSizeLimit = int.MaxValue,
    };

    public static readonly OpenAIClientOptions ClientOptions = new()
    {
        Endpoint = new Uri("http://localhost:1234/v1"),
        NetworkTimeout = TimeSpan.FromMinutes(10),
        ClientLoggingOptions = LoggingOptions,
    };

    public static OpenAIClient CreateClient() => new(new ApiKeyCredential("lm-studio"), ClientOptions);

    public static async Task<List<string>> GetAvailableModels(OpenAIClient client)
    {
        OpenAIModelCollection? models = (await client.GetOpenAIModelClient().GetModelsAsync())?.Value;
        return models is null ? [] : models.Select(m => m.Id).ToList();
    }

    public static void PrintModels(List<string> models)
    {
        Console.WriteLine($"Available {models.Count} model(s):");
        foreach (string model in models)
            Console.WriteLine(model);
    }
}

public sealed class MyLoggerFactory: ILoggerFactory
{
    public void Dispose()
    {
    }

    public ILogger CreateLogger(string categoryName) => new MyLogger();

    public void AddProvider(ILoggerProvider provider)
    {
    }
}

public sealed class MyLogger: ILogger
{
    public void Log<TState>(LogLevel logLevel, EventId eventId, TState state, Exception? exception,
        Func<TState, Exception?, string> formatter)
    {
        ConsoleColor color = logLevel switch
        {
            LogLevel.Trace => ConsoleColor.Gray,
            LogLevel.Debug => ConsoleColor.DarkGray,
            LogLevel.Information => ConsoleColor.White,
            LogLevel.Warning => ConsoleColor.Yellow,
            LogLevel.Error => ConsoleColor.Red,
            LogLevel.Critical => ConsoleColor.DarkRed,
            _ => ConsoleColor.White,
        };

        ConsoleColor oldColor = Console.ForegroundColor;
        Console.ForegroundColor = color;

        object? newState = state;
        if (newState is IReadOnlyList<KeyValuePair<string, object?>> stateProperties)
        {
            string json = string.Empty;
            int entryIndex = -1;
            for (int index = 0; index < stateProperties.Count; index++)
            {
                KeyValuePair<string, object?> entry = stateProperties[index];
                if (entry is { Key: "content", Value: string jsonString })
                {
                    json = GetFormattedJson(jsonString);
                    entryIndex = index;
                    break;
                }
            }

            if (entryIndex >= 0)
            {
                FieldInfo? field = typeof(TState).GetField($"_value{entryIndex}",
                    BindingFlags.GetField | BindingFlags.Instance | BindingFlags.NonPublic);

                field?.SetValue(newState, json);
            }
        }

        Console.WriteLine(formatter((TState)newState!, exception));

        Console.ForegroundColor = oldColor;
    }

    public bool IsEnabled(LogLevel logLevel) => true;

    public IDisposable BeginScope<TState>(TState state)
        where TState: notnull =>
        new Scope();

    private sealed class Scope: IDisposable
    {
        public void Dispose()
        {
        }
    }

    private static string GetFormattedJson(string jsonString)
    {
        try
        {
            using JsonDocument doc = JsonDocument.Parse(jsonString);
            string formatted = JsonSerializer.Serialize(
                doc.RootElement,
                new JsonSerializerOptions { WriteIndented = true }
            );

            return formatted;
        }
        catch (JsonException)
        {
            return jsonString;
        }
    }
}

[ZaneNi]

@antrv Hi, thanks for you feedback! We just released the newest version.

Could you please give it another try when you have a chance?

[antrv]

I have the same response in v0.9.43.
v0.9.43 also does not use appropriate tools.

[antrv]

If you want, I can give you the first http request.

POST http://localhost:1234/v1/chat/completions

{
  "temperature": 0.1,
  "messages": [
    {
      "role": "system",
      "content": "# Role and Environment\r\nYou are an autonomous AI orchestration agent running in a local environment. \r\nYour primary function is to fulfill user requests by effectively using your available tools and \r\ndiscovering specialized workflows called \u0022Skills.\u0022\r\n\r\n# Available Tools \u0026 Their Usage\r\nYou have access to the following tools. Never hallucinate tools outside of this list.\r\n- \u0060get_time\u0060: Use this if the user asks for the current date/time, or if a task requires scheduling context.\r\n- \u0060list_directory\u0060: Use this to explore folders. **CRITICAL:** Use this on the \u0060.skills\u0060 directory if you need to discover available specialized workflows.\r\n- \u0060read_file\u0060: Use this to read file contents. **CRITICAL:** Use this to read \u0060.skills/\u003Cskill_name\u003E/SKILL.md\u0060 files to learn how to execute a specific skill.\r\n- \u0060write_file\u0060: Use this to create entirely new files or completely overwrite existing ones.\r\n- \u0060edit_file\u0060: Use this to modify a specific section of an existing file using a search-and-replace text match. \r\n\r\n# The \u0022Skill Discovery\u0022 Workflow (Progressive Disclosure)\r\nYou do not know everything upfront. If the user asks for a complex task, a specific company workflow, or a specialized process, you MUST follow this sequence:\r\n1. **Discover:** Call \u0060list_directory\u0060 on the path \u0060.skills\u0060. \r\n2. **Identify:** Look at the returned folder names. Choose the one that best matches the user\u0027s request.\r\n3. **Learn:** Call \u0060read_file\u0060 on \u0060.skills/\u003Cchosen_folder\u003E/SKILL.md\u0060.\r\n4. **Execute:** Read the instructions provided in the \u0060SKILL.md\u0060 file and use your file t"
    },
    {
      "role": "user",
      "content": "I want to buy bread, eggs and milk. Add the task to the todo list"
    }
  ],
  "model": "gemma4-it:e4b",
  "tools": [
    {
      "type": "function",
      "function": {
        "description": "Returns the current time. Use this when the user\u0027s request is time-sensitive or relates to scheduling.",
        "name": "get_time"
      }
    },
    {
      "type": "function",
      "function": {
        "description": "Lists files/folders. REQUIRED for \u0027Skill Discovery\u0027: check the \u0027.skills\u0027 folder to see what specialized skills are available.",
        "name": "list_directory",
        "parameters": {
          "type": "object",
          "properties": {
            "path": {
              "type": "string",
              "description": "Path to list (e.g. \u0027.skills\u0027 or \u0027./project\u0027)"
            }
          },
          "required": [
            "path"
          ]
        }
      }
    },
    {
      "type": "function",
      "function": {
        "description": "Reads file content. REQUIRED for \u0027Skill Activation\u0027: read the \u0027.skills/\u003Cname\u003E/SKILL.md\u0027 file to learn how to perform a specific task.",
        "name": "read_file",
        "parameters": {
          "type": "object",
          "properties": {
            "path": {
              "type": "string",
              "description": "Relative path to the file."
            }
          },
          "required": [
            "path"
          ]
        }
      }
    },
    {
      "type": "function",
      "function": {
        "description": "Creates a new file or overwrites an existing one with new content.",
        "name": "write_file",
        "parameters": {
          "type": "object",
          "properties": {
            "path": {
              "type": "string",
              "description": "Path where the file should be saved."
            },
            "content": {
              "type": "string",
              "description": "The full text content to write."
            }
          },
          "required": [
            "path",
            "content"
          ]
        }
      }
    },
    {
      "type": "function",
      "function": {
        "description": "Updates a specific section of a file using a search-and-replace pattern.",
        "name": "edit_file",
        "parameters": {
          "type": "object",
          "properties": {
            "path": {
              "type": "string",
              "description": "Path to the file to edit."
            },
            "search_text": {
              "type": "string",
              "description": "The exact string currently in the file that needs to change."
            },
            "replacement_text": {
              "type": "string",
              "description": "The new text to put in place of the search_text."
            }
          },
          "required": [
            "path",
            "search_text",
            "replacement_text"
          ]
        }
      }
    }
  ]
}

[antrv]

Also sometimes FLM server return error response to this request (~ in 1/2 attempts):

{
  "error": {
    "message": "[json.exception.type_error.302] type must be string, but is object",
    "type": "server_error",
    "code": 500
  }
}

This happens when the raw model output is

[FLM]  Model RAW Output:
<|tool_call>call:write_file{content:<|"|>- Buy bread, eggs and milk<|"|>,path:<|"|>todo.txt<|"|>}<tool_call|>

Which is also not what I expect

[ZaneNi]

Also sometimes FLM server return error response to this request (~ in 1/2 attempts):

{
  "error": {
    "message": "[json.exception.type_error.302] type must be string, but is object",
    "type": "server_error",
    "code": 500
  }
}

This happens when the raw model output is

[FLM]  Model RAW Output:
<|tool_call>call:write_file{content:<|"|>- Buy bread, eggs and milk<|"|>,path:<|"|>todo.txt<|"|>}<tool_call|>

Which is also not what I expect

@antrv It looks like you are using non-stream mode. I apologize that tool calling in non-stream mode was not processed correctly before as the stream mode. This has been addressed by the patch here: https://github.com/FastFlowLM/FastFlowLM/actions/runs/26535836911

However, if the model refuses to call tools, that is likely the model’s native behavior and may be related to sampling or other model-side settings.

[antrv]

Thank you @ZaneNi , I'll wait until the patched version is released.

Please take a look at the first message. The behavior of the same model in llama.cpp is what I expect. I understand there may be some differences in quantization, etc. but the model itself is fully capable of using tools and following direct instructions in workflows.

[ZaneNi]

Thank you @ZaneNi , I'll wait until the patched version is released.

Please take a look at the first message. The behavior of the same model in llama.cpp is what I expect. I understand there may be some differences in quantization, etc. but the model itself is fully capable of using tools and following direct instructions in workflows.

May I ask which quantization you were using in llama.cpp?

[antrv]

Q4_K_M

https://huggingface.co/ggml-org/gemma-4-E4B-it-GGUF/tree/main

[ZaneNi]

Q4_K_M

https://huggingface.co/ggml-org/gemma-4-E4B-it-GGUF/tree/main

The weights in FLM was converted from

https://huggingface.co/unsloth/gemma-4-E4B-it-GGUF/blob/main/gemma-4-E4B-it-Q4_1.gguf

[antrv]

Thank you, I will check this model with my workflow as soon as I have the chance

[antrv]

@ZaneNi I tested the model unsloth/gemma-4-E4B-it-GGUF specifically in quantization Q4_1 (your link) with llama.cpp server. The behavior matches my expectations and it also differs from FFLM.

You: I need to buy bread, eggs and milk. Add the task to the todo list 
  → list_directory({"path":".skills"})
  ← {
  "directory": ".skills",
  "subdirectories": [
    "task-manager"
  ],
  "files": [],
  "message": "If you don\u0027t see the file you need, check subdirectories."
}
  → read_file({"path":".skills/task-manager/SKILL.md"})
  ← SKILL.md content
  → read_file({"path":"tasks.md"})
  ← { "error": "File not found: tasks.md" }
  → write_file({"content":"# My Tasks\n- [ ] Bread\n- [ ] Eggs\n- [ ] Milk","path":"tasks.md"})
  ← { "status": "success", "message": "File saved to tasks.md." }
Model: I have added "bread", "eggs", and "milk" to your todo list in `tasks.md`.

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