```                   # 📋 Session Report
    λλ              
   λ⊙λ⊙             
  λλλλλλ            
 λλλλλλλλ           
    λλ              
    λλ              
    λλ              
    λλ              
    λλ              
    λλ              
    λλ              
    λλ              
```                 

**🔑 Session ID:** 97308253-f584-43d6-8d69-dcadda655bf9

---

## 📊 Statistics

### Turn Counts

| Metric | Value |
|--------|-------|
| Total Turns | 28 |
| 👤 User Turns | 14 |
| 🤖 LLM Turns | 14 |

### 🔧 Tool Calls

**Total Tool Calls:** 19

`bash_read-file      `   10 ████████████████████████████████████████████████████████████

`bash_write-file     `    5 ██████████████████████████████

`bash_check-code     `    2 ████████████

`bash_grep-files     `    1 ██████

`bash_list-files     `    1 ██████


### 💾 Byte Usage

`Input     `    255 KiB ████████████████████████████████████████████████████████████

`Output    `      3 KiB 

`Reasoning `      4 KiB 
**Total:** 262 KiB

---

## 👤 Step 1: User Turn

### 📝 System Prompt

```
You are an expert Haskell and Bash programmer specialized in writing clean, idiomatic, and efficient Haskell code.
When writing Bash code:
- Avoid bash-specific logic but bash-ism are fine.
- Document required shell tools at the top of the bash script.
When writing Haskell code:
- Use modern Haskell practices (base >= 4.14)
- Prefer pure functions and explicit type signatures
- Use standard libraries when appropriate
- Add clear comments for complex logic
- Follow consistent formatting
Use list-files to explore the project structure, read-file to understand existing code, write-file to create or modify files, and check-code to verify your work.
Always compile code before considering the job done.
Your output format may be stored as commit message: hence the first line of your last message should be a summary line.
```

### 💬 User Query

# Handle binary tool outputs and support base64-encoded media attachments

Depends-on: 
Base-branch: main
Final: false

## Problem Statement

When a tool returns binary data (e.g., images, PDFs, or any non-UTF-8 content), the program crashes because `Text.decodeUtf8` throws an exception on invalid UTF-8 byte sequences. This affects multiple parts of the codebase:

1. **Critical crash locations:**
   - `src/System/Agents/OneShot.hs`: `BlobToolSuccess _ v -> UserToolResponse $ Aeson.String $ Text.decodeUtf8 v`
   - `src/System/Agents/MCP/Server.hs`: Similar pattern with `TextEncoding.decodeUtf8 v`
   - `src/System/Agents/Tools/Bash.hs`: `let outText = Text.decodeUtf8 out`
   - `src/System/Agents/Tools/OpenAPIToolbox.hs`: `Text.decodeUtf8 (LByteString.toStrict body)` in response handling
   - `src/System/Agents/Tools/PostgRESToolbox.hs`: Similar pattern in `handleResponse`

2. **Current `UserToolResponse` limitation:**
   ```haskell
   newtype UserToolResponse = UserToolResponse Aeson.Value
   ```
   This type can only represent JSON-compatible data. Binary data like images must be base64-encoded to be included.

## Proposed Solution

### Phase 1: Safe UTF-8 Decoding with Error Handling

Replace all `Text.decodeUtf8` calls on tool outputs with `Text.decodeUtf8With` using the `lenientDecode` strategy or explicit error handling:

```haskell
-- Instead of:
Text.decodeUtf8 bytes

-- Use:
import Data.Text.Encoding.Error (lenientDecode)
Text.decodeUtf8With lenientDecode bytes  -- Replaces invalid bytes with U+FFFD

-- Or for explicit handling:
case Text.decodeUtf8' bytes of
    Left err -> -- Return error message or base64-encode
    Right txt -> -- Use text
```

**Files to modify:**
- `src/System/Agents/OneShot.hs` - `callResultToUserToolResponse` function
- `src/System/Agents/MCP/Server.hs` - `callResultToUserToolResponse` function
- `src/System/Agents/Tools/Bash.hs` - `runValue` function
- `src/System/Agents/Tools/OpenAPIToolbox.hs` - `handleResponse` function
- `src/System/Agents/Tools/PostgRESToolbox.hs` - `handleResponse` function

### Phase 2: Support Base64-Encoded Media Attachments

Extend `UserToolResponse` to support structured content that can include media:

```haskell
-- New types for media support
data MediaType
    = MediaImage ImageType
    | MediaAudio AudioType
    | MediaVideo VideoType
    | MediaApplication ApplicationType
    | MediaText TextSubtype
    deriving (Show, Eq)

data ImageType = ImagePNG | ImageJPEG | ImageGIF | ImageWebP | ImageSVG
    deriving (Show, Eq)

data MediaAttachment = MediaAttachment
    { mediaType :: MediaType
    , mediaBase64Data :: Text  -- Base64-encoded content
    , mediaFilename :: Maybe Text
    } deriving (Show, Eq)

-- Extended UserToolResponse
data UserToolResponse
    = TextResponse Text
    | JsonResponse Aeson.Value
    | MediaResponse MediaAttachment
    | MixedResponse [ContentPart]  -- For multi-modal responses
    deriving (Show, Eq)

data ContentPart
    = TextPart Text
    | MediaPart MediaAttachment
    deriving (Show, Eq)
```

**Key design decisions to consider:**

1. **Auto-detection vs explicit marking**: Should tools mark their output as binary/media, or should we auto-detect based on content-type or magic bytes?

2. **MIME type handling**: How do we determine the media type? Options:
   - Add MIME type to `BlobToolSuccess` constructor
   - Use `file` command or magic byte detection
   - Let tools self-declare their output type in `ScriptInfo`

3. **LLM compatibility**: Different LLMs have different support for media:
   - OpenAI: Supports base64 images in specific formats
   - Claude: Supports images via base64
   - Other models may vary

4. **Base64 encoding**: Follow the pattern already used in `src/System/Agents/ExportImport/Types.hs`:
   ```haskell
   import qualified Data.ByteString.Base64 as B64
   Text.decodeUtf8 (B64.encode bytes)  -- For encoding
   B64.decode (Text.encodeUtf8 text)   -- For decoding
   ```

## Trade-offs Analysis

### Option A: Lenient decoding only (minimal change)
- **Pros**: Simple, no API changes, prevents crashes
- **Cons**: Binary data becomes garbled text (U+FFFD replacement characters), LLM sees garbage

### Option B: Base64 encoding for all binary (safe but verbose)
- **Pros**: Always safe, no data loss
- **Cons**: Text output becomes unreadable when not needed, increases token count

### Option C: Smart detection with explicit binary marking (recommended)
- **Pros**: Best UX, supports media properly, backwards compatible
- **Cons**: More complex, requires tool schema changes

### Option D: Content-Type aware (most complete)
- **Pros**: Follows HTTP conventions, supports media types natively
- **Cons**: Requires significant refactoring of tool definitions

## Implementation Notes

1. **Current base64 usage in codebase**: `ExportImport/Types.hs` already uses `Data.ByteString.Base64` for encoding tool scripts. This pattern should be reused.

2. **HTTP response handling**: `OpenAPIToolbox` and `PostgRESToolbox` receive `Content-Type` headers which could be used to determine if content should be base64-encoded.

3. **Bash tool considerations**: Bash scripts don't have content-type metadata. Options:
   - Add `scriptOutputMediaType` field to `ScriptInfo`
   - Auto-detect via file magic bytes
   - Always use lenient UTF-8 for bash tools

## Acceptance Criteria

- [ ] All `Text.decodeUtf8` calls on tool outputs use safe decoding strategies
- [ ] Binary tool outputs no longer cause program crashes
- [ ] Media attachments can be represented in `UserToolResponse`
- [ ] Base64-encoded images can be passed to LLMs that support them
- [ ] Existing text-based tools continue to work unchanged
- [ ] Test cases for binary output handling

## Related Code Patterns

The `ExportImport/Types.hs` module already demonstrates safe base64 handling:
```haskell
instance ToJSON ToolExport where
    toJSON te =
        Aeson.object $
            [ "name" .= te.toolName
            , "content_base64" .= Text.decodeUtf8 (B64.encode te.toolContent)
            ...

instance FromJSON ToolExport where
    parseJSON = Aeson.withObject "ToolExport" $ \v -> do
        contentB64 <- v .: "content_base64"
        let decoded = B64.decode (Text.encodeUtf8 contentB64)
        case decoded of
            Left err -> fail $ "Invalid base64 content: " ++ show err
            Right content -> ...
```

## Next Steps

1. Decide on the preferred approach (A, B, C, or D above)
2. Implement Phase 1 (safe UTF-8 decoding) as immediate fix
3. Design and implement Phase 2 (media attachments) based on the chosen approach
4. Update tool schemas to optionally declare output media types
5. Add tests with binary data fixtures

---
From #265



### 🛠️ Available Tools

- **bash_grep-files** (`bash_grep-files`)
  - Description: Search for a pattern in files using 'git grep'
- **bash_read-file** (`bash_read-file`)
  - Description: Read the contents of a file
- **bash_write-file** (`bash_write-file`)
  - Description: Write content to a file
- **bash_check-code** (`bash_check-code`)
  - Description: Check Haskell code by compiling or testing
- **bash_list-files** (`bash_list-files`)
  - Description: List all files in the project

---

## 🤖 Step 2: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

The user wants me to implement a solution to handle binary tool outputs and support base64-encoded media attachments in a Haskell codebase. Let me start by exploring the project structure and understanding the existing code.

The problem is that `Text.decodeUtf8` throws exceptions on invalid UTF-8 byte sequences when tools return binary data like images or PDFs.

Let me first explore the project structure and understand the codebase.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_list-files**

---

## 👤 Step 3: User Turn



---

## 🤖 Step 4: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

Now let me look at the files mentioned in the issue. Let me start by reading the key files that need modification:
1. src/System/Agents/OneShot.hs
2. src/System/Agents/MCP/Server.hs
3. src/System/Agents/Tools/Bash.hs
4. src/System/Agents/Tools/OpenAPIToolbox.hs
5. src/System/Agents/Tools/PostgRESToolbox.hs
6. src/System/Agents/ExportImport/Types.hs (for reference on base64 handling)
</details>

### 💬 Response

Let me examine the key files mentioned in the issue to understand the current code structure:

### 🔧 Tool Calls

- **bash_read-file**

- **bash_read-file**

- **bash_read-file**

- **bash_read-file**

---

## 👤 Step 5: User Turn



---

## 🤖 Step 6: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

Now let me look at the OpenAPIToolbox and PostgRESToolbox files to understand the current handling of binary data in HTTP responses:
</details>

### 💬 Response

Now let me read the other files mentioned in the issue:

### 🔧 Tool Calls

- **bash_read-file**

- **bash_read-file**

- **bash_read-file**

---

## 👤 Step 7: User Turn



---

## 🤖 Step 8: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

Now I have a good understanding of the codebase. Let me also look at the Session/Base.hs file to understand UserToolResponse and how it's used:
</details>

### 💬 Response

Let me also check the Session/Base.hs file to understand the UserToolResponse type:

### 🔧 Tool Calls

- **bash_read-file**

- **bash_grep-files**

---

## 👤 Step 9: User Turn



---

## 🤖 Step 10: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

Now let me look at the Session.Types to understand the UserToolResponse type:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_read-file**

---

## 👤 Step 11: User Turn



---

## 🤖 Step 12: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

Now I have a good understanding of the problem. Let me summarize the key findings:

1. **Critical crash locations identified:**
   - `src/System/Agents/OneShot.hs`: `BlobToolSuccess _ v -> UserToolResponse $ Aeson.String $ Text.decodeUtf8 v`
   - `src/System/Agents/MCP/Server.hs`: Similar pattern with `TextEncoding.decodeUtf8 v`
   - `src/System/Agents/Tools/Bash.hs`: `let outText = Text.decodeUtf8 out`
   - `src/System/Agents/Tools/OpenAPIToolbox.hs`: `Text.decodeUtf8 (LByteString.toStrict body)` in response handling
   - `src/System/Agents/Tools/PostgRESToolbox.hs`: Similar pattern in `handleResponse`

2. The `UserToolResponse` is currently a newtype wrapper around `Aeson.Value`:
   ```haskell
   newtype UserToolResponse = UserToolResponse Aeson.Value
   ```

3. The issue is that `Text.decodeUtf8` throws an exception on invalid UTF-8 byte sequences.

Based on the problem statement, I need to implement **Phase 1** first - safe UTF-8 decoding with error handling. The recommended approach is to use `Text.decodeUtf8With lenientDecode` which replaces invalid bytes with U+FFFD (replacement character).

Let me now implement the solution. The key changes will be:

1. **In `src/System/Agents/OneShot.hs`**: Change `Text.decodeUtf8 v` to `Text.decodeUtf8With lenientDecode v`
2. **In `src/System/Agents/MCP/Server.hs`**: Change `TextEncoding.decodeUtf8 v` to `TextEncoding.decodeUtf8With lenientDecode v`


3. **In `src/System/Agents/Tools/Bash.hs`**: Change `Text.decodeUtf8 out` to `Text.decodeUtf8With lenientDecode out`
4. **In `src/System/Agents/Tools/OpenAPIToolbox.hs`**: Change `Text.decodeUtf8` calls to use `Text.decodeUtf8With lenientDecode`
5. **In `src/System/Agents/Tools/PostgRESToolbox.hs`**: Change `Text.decodeUtf8` calls to use `Text.decodeUtf8With lenientDecode`

I'll proceed with modifying these files to implement robust UTF-8 decoding that handles invalid byte sequences gracefully. This approach ensures that binary or malformed data won't cause unexpected runtime exceptions.
</details>

### 💬 Response

Now I have a clear understanding of the issue. Let me implement the fix using `Text.decodeUtf8With lenientDecode` to handle binary data safely. I'll modify all the critical locations:

### 🔧 Tool Calls

- **bash_read-file**

---

## 👤 Step 13: User Turn



---

## 🤖 Step 14: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

Good, the project uses `text` package. Now let me make the modifications to fix the unsafe `decodeUtf8` calls. I'll update each file:

1. `src/System/Agents/OneShot.hs` - use `decodeUtf8With lenientDecode`
2. `src/System/Agents/MCP/Server.hs` - use `decodeUtf8With lenientDecode` 
3. `src/System/Agents/Tools/Bash.hs` - use `decodeUtf8With lenientDecode`
4. `src/System/Agents/Tools/OpenAPIToolbox.hs` - use `decodeUtf8With lenientDecode`
5. `src/System/Agents/Tools/PostgRESToolbox.hs` - use `decodeUtf8With lenientDecode`
</details>

### 💬 Response

Now let me implement the safe UTF-8 decoding fix. I'll update each file to use `decodeUtf8With lenientDecode`:

### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 15: User Turn



---

## 🤖 Step 16: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

Good, now let me update the MCP/Server.hs file:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 17: User Turn



---

## 🤖 Step 18: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

Good, now let me update the Bash.hs file:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 19: User Turn



---

## 🤖 Step 20: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

Now let me update the OpenAPIToolbox.hs file:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 21: User Turn



---

## 🤖 Step 22: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

Now let me update the PostgRESToolbox.hs file:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 23: User Turn



---

## 🤖 Step 24: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

Now let me compile the code to make sure there are no errors:
</details>

### 💬 Response

Now let me compile the code to verify it works:

### 🔧 Tool Calls

- **bash_check-code**

---

## 👤 Step 25: User Turn



---

## 🤖 Step 26: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

The code compiles successfully. The warnings are pre-existing and unrelated to our changes. Now let me run the tests to make sure everything is working properly:
</details>

### 💬 Response

The code compiles successfully. Let me run the tests to make sure everything works:

### 🔧 Tool Calls

- **bash_check-code**

---

## 👤 Step 27: User Turn



---

## 🤖 Step 28: LLM Turn

### 💭 Thinking Process

<details>
<summary>Click to expand reasoning</summary>

All 270 tests pass. The implementation is complete. Let me provide a summary of the changes made.
</details>

### 💬 Response

All 270 tests pass. Let me provide a summary of the changes made:

## Summary

I've implemented **Phase 1** of the binary tool output handling as described in the issue. The changes replace all unsafe `Text.decodeUtf8` calls on tool outputs with `Text.decodeUtf8With lenientDecode`, which safely handles binary data by replacing invalid UTF-8 byte sequences with the U+FFFD replacement character (�).

### Files Modified

1. **`src/System/Agents/OneShot.hs`**
   - Added import for `Data.Text.Encoding.Error (lenientDecode)`
   - Changed `Text.decodeUtf8 v` to `Text.decodeUtf8With lenientDecode v` in `callResultToUserToolResponse` for `BlobToolSuccess`

2. **`src/System/Agents/MCP/Server.hs`**
   - Added import for `Data.Text.Encoding.Error (lenientDecode)`
   - Changed `TextEncoding.decodeUtf8 v` to `TextEncoding.decodeUtf8With lenientDecode v` in `callResultToUserToolResponse` for `BlobToolSuccess`

3. **`src/System/Agents/Tools/Bash.hs`**
   - Added import for `Data.Text.Encoding.Error (lenientDecode)`
   - Changed `Text.decodeUtf8 out` to `Text.decodeUtf8With lenientDecode out` in `runValue`
   - Changed session JSON encoding to use lenient decoding for safety

4. **`src/System/Agents/Tools/OpenAPIToolbox.hs`**
   - Added import for `Data.Text.Encoding.Error (lenientDecode)`
   - Changed `Text.decodeUtf8 (LByteString.toStrict body)` to `Text.decodeUtf8With lenientDecode (LByteString.toStrict body)` in `handleResponse` for both JSON payload fallback and text result

5. **`src/System/Agents/Tools/PostgRESToolbox.hs`**
   - Added import for `Data.Text.Encoding.Error (lenientDecode)`
   - Changed `Text.decodeUtf8 (LByteString.toStrict body)` to `Text.decodeUtf8With lenientDecode (LByteString.toStrict body)` in `handleResponse` for both JSON payload fallback and text result

### Key Design Decisions

- **Lenient decoding strategy**: Using `lenientDecode` replaces invalid bytes with U+FFFD (replacement character) rather than throwing exceptions. This is the safest immediate fix that prevents crashes while preserving as much readable text as possible.

- **Documentation**: Each modified location includes a comment explaining why lenient decoding is used and what happens to invalid bytes.

- **No API changes**: This is a minimal, non-breaking change that maintains backward compatibility. Existing text-based tools continue to work unchanged.

### Trade-offs (as noted in the issue)

This implementation chooses **Option A (Lenient decoding only)** as an immediate fix:
- **Pros**: Simple, no API changes, prevents crashes, backward compatible
- **Cons**: Binary data becomes garbled text (with � characters), LLM sees replacement characters

For **Phase 2** (future work), the codebase can be extended to support structured media attachments with base64 encoding, allowing proper handling of images and other binary content for LLMs that support them.
