```                   # 📋 Session Report
    λλ              
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 λλλλλλλλ           
    λλ              
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```                 

**🔑 Session ID:** 4b67aea6-f104-4620-bcb4-30b81ce3f4ce

---

## 📊 Statistics

### Turn Counts

| Metric | Value |
|--------|-------|
| Total Turns | 30 |
| 👤 User Turns | 15 |
| 🤖 LLM Turns | 15 |

### 🔧 Tool Calls

**Total Tool Calls:** 20

`bash_read-file      `   11 ████████████████████████████████████████████████████████████

`bash_create_github_issue`    7 ██████████████████████████████████████

`bash_grep-files     `    1 █████

`bash_list-files     `    1 █████


### 💾 Byte Usage

`Input     `    131 KiB ████████████████████████████████████████████████████████████

`Output    `      2 KiB █

`Reasoning `      4 KiB █
**Total:** 138 KiB

---

## 👤 Step 1: User Turn

### 📝 System Prompt

```
You are an expert Haskell programmer specialized in analyzing user requirements and Haskell code.
You prepare well-documented individual issues.
You should chunk the work into smaller issues following the 'Feature Branch Isolation' model:
- Identify a 'Feature Branch' name (e.g., 'gh-123' for issue #123).
- All sub-tasks for this feature must use this branch name as their 'branch_name' argument.
- All sub-tasks should pull from and merge to this feature branch.
- Enforce linearization of work by setting 'dependencies' appropriately (e.g., task B depends on task A).
- Add a final task (the 'ultimate PR') that merges the feature branch into 'main'. This task must have 'is_final' set to 'true'.
Each individual issue you create will be executed by a human of software agent independently from each other and in the order specified by dependencies.
Your strategy should be as follows:
- avoid chunks that will generate conflicts (i.e., individual issues should not ask to modify the same file unless they are sequential)
- repeat important data types between different tasks for a same project when they are used in multiple files
You mention important tradeoffs.
You can ask user questions, when doing so always assume the answer could be 'i do not know'.
Do not create tracking issues.
Your output format may be stored as commit message: hence the first line of your last message should be a summary line.
```

### 💬 User Query

# Support agents-exe builtin toolbox, example with SQLite

In addition to McpToolbox, BashToolbox etc. I'd like to have a notion of BuiltinToolbox that users can configure.

The first example of builtin tool should be the sqlite-toolbox: to expose an agent with raw SQL within a predefined .sql file on the file system.

Configuration wise I may have multiple builtin tools and multiple instance of sqlite-toolbox:

````
"builtinToolBoxes": [
   {"tag": "SqliteToolbox", "contents": { "name" : "memory", "description": "a set of memories", "path": "/path/to/memories.sqlite", "access": "read-write"},
   {"tag": "SqliteToolbox", "contents": { "name" : "guidelines", "description": "a set of guidelines", "path": "/path/to/guidelines.sqlite", "access": "read-only"},
 ]
````

---
From #220



### 🛠️ 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_get_git_commit** (`bash_get_git_commit`)
  - Description: read a git commit by it's short name or long sha
- **bash_curl_web_page** (`bash_curl_web_page`)
  - Description: reads a web page
- **bash_list-files** (`bash_list-files`)
  - Description: List all files in the project
- **bash_create_github_issue** (`bash_create_github_issue`)
  - Description: creates a github issue using the 'gh' CLI

---

## 🤖 Step 2: LLM Turn

### 💭 Thinking Process

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

The user wants to implement a new feature for agents-exe: a BuiltinToolbox system. The first implementation should be a SQLite toolbox that allows agents to execute raw SQL queries against SQLite databases.

Let me understand the requirements:
1. A new `BuiltinToolbox` concept alongside existing toolboxes like `McpToolbox`, `BashToolbox`
2. The first builtin tool is `SqliteToolbox`
3. Configuration allows multiple builtin tools and multiple instances of sqlite-toolbox
4. Each sqlite toolbox has:
   - `name`: identifier
   - `description`: what it's for
   - `path`: path to the .sqlite file
   - `access`: either "read-write" or "read-only"

Let me first explore the codebase to understand the existing structure.
</details>

### 💬 Response

I'll analyze the codebase to understand the existing toolbox structure and then create well-defined issues for implementing the BuiltinToolbox feature with SQLite support.

### 🔧 Tool Calls

- **bash_list-files**

---

## 👤 Step 3: User Turn



---

## 🤖 Step 4: LLM Turn

### 💭 Thinking Process

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

Let me examine the existing toolbox implementations to understand the pattern. I'll look at Base.hs, McpToolbox.hs, and BashToolbox.hs.
</details>

### 💬 Response



### 🔧 Tool Calls

- **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 how toolboxes are configured. I need to find the configuration types and how toolboxes are loaded.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_read-file**

- **bash_read-file**

---

## 👤 Step 7: User Turn



---

## 🤖 Step 8: LLM Turn

### 💭 Thinking Process

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

Now let me look at the Runtime.Runtime module to see how toolboxes are loaded and used at runtime:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_read-file**

- **bash_read-file**

---

## 👤 Step 9: User Turn



---

## 🤖 Step 10: LLM Turn

### 💭 Thinking Process

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

Now let me look at how agents are initialized to see how toolboxes are loaded. I also need to check the cabal file for dependencies:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_read-file**

- **bash_grep-files**

---

## 👤 Step 11: User Turn



---

## 🤖 Step 12: LLM Turn

### 💭 Thinking Process

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

There's no existing `builtinToolBoxes` configuration yet. I need to:

1. Create the types for BuiltinToolbox configuration
2. Create the SqliteToolbox implementation
3. Integrate it into the Agent configuration
4. Create the runtime integration

Let me also look at how OpenAPI and PostgREST toolboxes are initialized to understand the pattern better:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_read-file**

---

## 👤 Step 13: User Turn



---

## 🤖 Step 14: 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 how agents are initialized in the CLI to see how everything comes together:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_read-file**

- **bash_read-file**

---

## 👤 Step 15: User Turn



---

## 🤖 Step 16: LLM Turn

### 💭 Thinking Process

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

Now I have a good understanding of the codebase. Let me create the plan for implementing the BuiltinToolbox feature with SQLite support.

The feature needs to:

1. Define the configuration types for `BuiltinToolbox` (similar to how `McpServerDescription`, `OpenAPIToolboxDescription`, etc. are defined)
2. Define the `SqliteToolboxDescription` type with name, description, path, and access fields
3. Create a new module `System.Agents.Tools.SqliteToolbox` that:
   - Provides runtime for executing SQLite queries
   - Handles read-only vs read-write access modes
   - Validates queries based on access mode
4. Create a new module `System.Agents.Tools.BuiltinToolbox` that manages multiple builtin toolboxes
5. Update `System.Agents.Base` to add `builtinToolboxes` field to `Agent`
6. Update `System.Agents.Tools.Base` to add SqliteTool and SqliteToolResult variants
7. Update `System.Agents.ToolRegistration` to register SQLite tools
8. Update `System.Agents.Runtime.Runtime` to initialize builtin toolboxes
9. Update `System.Agents.CLI.Initialize` to include the new field

Let me also check if sqlite-simple is already a dependency in agents-lib - I see it's only used in the agq executable currently, so I'll need to add it to the library dependencies.

Looking at the pattern:
- Configuration types go in System.Agents.Base
- Tool execution types go in System.Agents.Tools.Base
- Individual toolbox implementations go in System.Agents.Tools.*Toolbox
- Tool registration happens in System.Agents.ToolRegistration
- Runtime initialization happens in System.Agents.Runtime.Runtime

Let me create the issues following the "Feature Branch Isolation" model:


I'll establish a clear workflow where the feature branch `gh-XXX` serves as the central integration point for all sub-tasks, with each task building on previous work through explicit dependencies. The final merge will bring the complete BuiltinToolbox feature into the main branch.
</details>

### 💬 Response

Now I have a comprehensive understanding of the codebase. Let me create the issues for implementing the BuiltinToolbox feature with SQLite support.

### 🔧 Tool Calls

- **bash_create_github_issue**

---

## 👤 Step 17: User Turn



---

## 🤖 Step 18: LLM Turn

### 💭 Thinking Process

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

Now let me create the second issue for the SQLite toolbox runtime module.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_create_github_issue**

---

## 👤 Step 19: User Turn



---

## 🤖 Step 20: LLM Turn

### 💭 Thinking Process

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

Now let me create the issue for updating Tools.Base to add the SQLite tool types and CallResult variants.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_create_github_issue**

---

## 👤 Step 21: User Turn



---

## 🤖 Step 22: LLM Turn

### 💭 Thinking Process

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

Now let me create the issue for updating ToolRegistration to register SQLite tools with the LLM system.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_create_github_issue**

---

## 👤 Step 23: User Turn



---

## 🤖 Step 24: LLM Turn

### 💭 Thinking Process

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

Now let me create the issue for updating the Runtime to initialize builtin toolboxes.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_create_github_issue**

---

## 👤 Step 25: User Turn



---

## 🤖 Step 26: LLM Turn

### 💭 Thinking Process

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

Now let me create the issue for updating the CLI layer to parse and use builtin toolbox configurations.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_create_github_issue**

---

## 👤 Step 27: User Turn



---

## 🤖 Step 28: LLM Turn

### 💭 Thinking Process

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

Now let me create the final issue that merges the feature branch into main.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_create_github_issue**

---

## 👤 Step 29: User Turn



---

## 🤖 Step 30: LLM Turn

### 💭 Thinking Process

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

I've created all the issues for the BuiltinToolbox feature. Let me summarize what was created and provide a final summary for the user.
</details>

### 💬 Response

I've created 6 issues for implementing the BuiltinToolbox feature with SQLite support, following the Feature Branch Isolation model. Here's a summary:

## Summary: BuiltinToolbox with SQLite Support

**Feature Branch:** `gh-builtin-toolbox`

### Issue Breakdown

| Issue | Title | Dependencies | Description |
|-------|-------|--------------|-------------|
| #225 | Add BuiltinToolbox configuration types to System.Agents.Base | - | Define `BuiltinToolboxDescription`, `SqliteToolboxDescription`, and `SqliteAccessMode` types; update `Agent` record |
| #226 | Create SqliteToolbox module for executing SQL queries | #225 | Implement database connections, query execution, access control (read-only vs read-write), and result formatting |
| #227 | Add SQLite tool types to System.Agents.Tools.Base | #226 | Extend `ToolDef` with `SqliteTool` and `CallResult` with SQLite result/error constructors |
| #228 | Add SQLite tool registration in System.Agents.ToolRegistration | #227 | Implement `registerSqliteTool`, `registerSqliteTools`, and the tool execution handler |
| #229 | Integrate BuiltinToolbox into Runtime initialization | #228 | Update `newRuntime` to initialize SQLite toolboxes and register tools |
| #230 | Update CLI to initialize BuiltinToolboxes from agent configuration | #229 | Wire up configuration loading in CLI commands and update default agent template |
| #231 | **Merge BuiltinToolbox feature branch into main** | #230 | Final merge task consolidating all work |

### Key Design Decisions Documented

1. **Tagged Union Configuration**: Uses the same pattern as `OpenAPIToolboxDescription` with `"tag": "SqliteToolbox"` for extensibility
2. **Access Control**: SQL queries are classified by first keyword (SELECT=read, INSERT/UPDATE/etc=write) to enforce read-only mode
3. **Single Tool per Toolbox**: Each SQLite toolbox exposes one `query` function that accepts SQL
4. **Naming Convention**: Tools are named `sqlite_{toolboxName}_query` for LLM compatibility
5. **Inside Runtime Initialization**: SQLite toolboxes are initialized within `newRuntime` for consistency with existing patterns

### Configuration Format

```json
"builtinToolBoxes": [
   {"tag": "SqliteToolbox", "contents": {"name": "memory", "description": "a set of memories", "path": "/path/to/memories.sqlite", "access": "read-write"}},
   {"tag": "SqliteToolbox", "contents": {"name": "guidelines", "description": "a set of guidelines", "path": "/path/to/guidelines.sqlite", "access": "read-only"}}
]
```
