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

**🔑 Session ID:** b2d63224-e44b-4f26-8833-271b47c308a1

---

## 📊 Statistics

### Turn Counts

| Metric | Value |
|--------|-------|
| Total Turns | 50 |
| 👤 User Turns | 25 |
| 🤖 LLM Turns | 25 |

### 🔧 Tool Calls

**Total Tool Calls:** 30

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

`bash_check-code     `    8 ███████████████████████████████████████████

`bash_write-file     `    8 ███████████████████████████████████████████

`bash_grep-files     `    2 ██████████

`bash_list-files     `    1 █████


### 💾 Byte Usage

`Input     `    333 KiB ████████████████████████████████████████████████████████████

`Output    `      2 KiB 

`Reasoning `      5 KiB █
**Total:** 342 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

# Create SqliteToolbox module for executing SQL queries

Depends-on: #225
Base-branch: gh-builtin-toolbox
Final: false

## Task

Create the `System.Agents.Tools.SqliteToolbox` module that provides runtime for executing SQL queries against SQLite databases.

## Background

This module implements the actual SQLite toolbox functionality, including:
- Database connection management
- Query execution with access control (read-only vs read-write)
- Result formatting for LLM consumption
- Tracing for debugging and monitoring

## Module Structure

```haskell
module System.Agents.Tools.SqliteToolbox where

-- Core types
data Trace = ...  -- Trace events for operations
data Toolbox = Toolbox { ... }  -- Runtime state
data QueryError = ...  -- Error types

-- Access control validation
data AccessMode = ReadOnly | ReadWrite
data SqlOperation = Select | Insert | Update | Delete | Create | Drop | Alter | Other
  deriving (Eq, Show)

classifyQuery :: Text -> SqlOperation
allowsOperation :: AccessMode -> SqlOperation -> Bool
validateAccess :: AccessMode -> Text -> Either QueryError ()

-- Initialization
initializeToolbox :: Tracer IO Trace -> SqliteToolboxDescription -> IO (Either String Toolbox)

-- Query execution
executeQuery :: Toolbox -> Text -> IO (Either QueryError QueryResult)
executeReadOnlyQuery :: Toolbox -> Text -> IO (Either QueryError QueryResult)
executeWriteQuery :: Toolbox -> Text -> IO (Either QueryError QueryResult)

-- Result formatting
formatResults :: QueryResult -> ByteString
```

## Key Features

1. **Access Control**: Parse SQL queries to determine if they're read-only operations (SELECT) or write operations (INSERT, UPDATE, DELETE, CREATE, DROP, ALTER). Reject write operations when toolbox is configured as read-only.

2. **Query Classification**: Implement a simple SQL classifier that examines the first keyword of a query to determine the operation type.

3. **Result Formatting**: Return results as JSON with:
   - Column names
   - Row data as arrays or objects
   - Row count
   - Execution time (optional)

4. **Connection Management**: Use sqlite-simple for database connections. Each toolbox maintains its own connection.

## Dependencies

Add `sqlite-simple` to the library dependencies in `agents.cabal`:

```cabal
build-depends:    ...
                  sqlite-simple,
                  ...
```

## Implementation Notes

- Use `Database.SQLite.Simple` for database operations
- Use `Text` for SQL queries (sqlite-simple supports Text)
- Format results as JSON for consistency with other tool types
- Include proper error handling for SQL syntax errors, database errors, and access violations
- Trace key events: query execution start/end, access violations, errors

## SQL Classification Rules

Simple approach: examine first non-whitespace, non-comment token:
- SELECT -> Select
- INSERT -> Insert  
- UPDATE -> Update
- DELETE -> Delete
- CREATE -> Create
- DROP -> Drop
- ALTER -> Alter
- Other -> Other (will be rejected in read-only mode, allowed in read-write)

## Files to Create

- `src/System/Agents/Tools/SqliteToolbox.hs`

## Files to Modify

- `agents.cabal` - add `sqlite-simple` to library dependencies

## Testing

- Test query classification with various SQL statements
- Test access control enforcement
- Test error handling for invalid SQL

---
From #226



### 🛠️ 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>

Let me start by exploring the project structure to understand the codebase better.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_list-files**

---

## 👤 Step 3: User Turn



---

## 🤖 Step 4: LLM Turn

### 💭 Thinking Process

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

Let me look at existing toolbox implementations to understand the patterns used in this codebase. I'll check BashToolbox.hs and the Tools/Base.hs to understand the structure.
</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 some other toolbox implementations to understand patterns better. Let me check PostgRESToolbox and OpenAPIToolbox to see how they handle query execution and results.
</details>

### 💬 Response



### 🔧 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 patterns used. Let me also look at how IO tools are structured, as that might be similar to what we need for SQLite:
</details>

### 💬 Response

Now let me look at the IO tools and see how error handling is done:

### 🔧 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 check the Base.hs file to see how SqliteToolboxDescription is defined, and also see the test file to understand how it should be used:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_read-file**

- **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 codebase. Let me now create the `SqliteToolbox.hs` module. Based on the requirements and patterns I've seen:

1. I need to create the module at `src/System/Agents/Tools/SqliteToolbox.hs`
2. I need to add `sqlite-simple` to the cabal file dependencies
3. The module should include:
   - Trace types for operations
   - Toolbox type for runtime state
   - QueryError type for errors
   - AccessMode and SqlOperation types for access control
   - classifyQuery, allowsOperation, validateAccess functions
   - initializeToolbox function
   - executeQuery, executeReadOnlyQuery, executeWriteQuery functions
   - formatResults function

Let me also check if there's anything about the expected output format that should match other toolboxes.

From looking at the existing toolboxes:
- BashToolbox returns raw ByteString
- PostgRESToolbox returns structured ToolResult as JSON
- For SQLite, based on the spec, I should return JSON formatted results

Let me now implement the module:
</details>

### 💬 Response

Now I have a good understanding of the codebase patterns. Let me create the `SqliteToolbox` module and update the cabal file.

### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 13: User Turn



---

## 🤖 Step 14: LLM Turn

### 💭 Thinking Process

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

Now I need to update the cabal file to add `sqlite-simple` to the library dependencies and add the new module to the exposed-modules list.
</details>

### 💬 Response

Now let me update the cabal file to add the `sqlite-simple` dependency and expose the new module:

### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 15: User Turn



---

## 🤖 Step 16: LLM Turn

### 💭 Thinking Process

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

Now let me try to compile the code to check for any errors:
</details>

### 💬 Response

Now let's compile the code to check for any issues:

### 🔧 Tool Calls

- **bash_check-code**

---

## 👤 Step 17: User Turn



---

## 🤖 Step 18: LLM Turn

### 💭 Thinking Process

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

There are several issues with my implementation:

1. `SQLite.NamedRow` doesn't exist - I need to use a different approach to get results with column names
2. `SQLite.fieldName`, `SQLite.rowFields`, `SQLite.fieldData` don't exist
3. `Aeson.fromText` doesn't exist - should be `Aeson.Key.fromText`

I need to rewrite the query execution to use a different approach with sqlite-simple. Let me check how sqlite-simple actually works and rewrite the module accordingly.

For sqlite-simple, a common approach is to:
1. Use `query_` with a custom FromRow instance
2. Or use the lower-level `fold_` function
3. Or use `withStatement` and manually extract fields

Actually, let me look at the sqlite-simple API more carefully. The library provides:
- `query_` which returns rows that can be converted
- `fold_` for folding over results
- `withStatement` for low-level access

I think the best approach is to use `withStatement` which gives access to the column names and field data. Let me rewrite the module.
</details>

### 💬 Response

I need to fix the implementation - sqlite-simple doesn't have the `NamedRow` API I was trying to use. Let me rewrite the module using a different approach that works with sqlite-simple:

### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 19: User Turn



---

## 🤖 Step 20: LLM Turn

### 💭 Thinking Process

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

Now I need to add `direct-sqlite` to the cabal file as a dependency since I'm using the lower-level API. Let me update the cabal file:
</details>

### 💬 Response

Now I need to add the `direct-sqlite` dependency to the cabal file:

### 🔧 Tool Calls

- **bash_read-file**

---

## 👤 Step 21: User Turn



---

## 🤖 Step 22: LLM Turn

### 💭 Thinking Process

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

The `sqlite-simple` package already includes `direct-sqlite` as a transitive dependency, so I should be able to use `Database.SQLite3`. Let me try compiling to see if it works.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_check-code**

---

## 👤 Step 23: User Turn



---

## 🤖 Step 24: LLM Turn

### 💭 Thinking Process

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

I need to add direct-sqlite to the cabal file. Let me update it:
</details>

### 💬 Response

I need to add `direct-sqlite` as a dependency:

### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 25: User Turn



---

## 🤖 Step 26: LLM Turn

### 💭 Thinking Process

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

Let me try compiling again:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_check-code**

---

## 👤 Step 27: User Turn



---

## 🤖 Step 28: LLM Turn

### 💭 Thinking Process

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

The `Connection` constructor is not exported from `Database.SQLite3`. Let me check the sqlite-simple API to see how I can get access to the underlying connection handle.Looking at the sqlite-simple API, I need to use a different approach. I should use `fold_` with a custom function that can collect rows and column names. But wait, `fold_` also doesn't give me column names directly.

A better approach would be to:
1. Use `withStatement` which provides access to the statement and its metadata2. Or use the lower-level direct-sqlite API with the connection string directly

Let me look at a simpler approach - I'll use direct-sqlite directly for the query execution since we need column metadata.
</details>

### 💬 Response

The `Connection` constructor isn't exported. Let me use direct-sqlite directly instead:

### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 29: User Turn



---

## 🤖 Step 30: LLM Turn

### 💭 Thinking Process

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

Now let me try compiling again:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_check-code**

---

## 👤 Step 31: User Turn



---

## 🤖 Step 32: LLM Turn

### 💭 Thinking Process

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

I need to qualify the column type constructors since they're imported from the `Database.SQLite3` module but are conflicting with other imports. Let me fix this:
</details>

### 💬 Response

I need to qualify the column type constructors:

### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 33: User Turn



---

## 🤖 Step 34: LLM Turn

### 💭 Thinking Process

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

Now let me try compiling again:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_check-code**

---

## 👤 Step 35: User Turn



---

## 🤖 Step 36: LLM Turn

### 💭 Thinking Process

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

There are several type issues I need to fix:

1. `Direct.open` expects `Text`, not `FilePath` (String)2. `Tracer` is a type constructor, not a data constructor - I need to use the proper function from Prod.Tracer
3. `Direct.columnName` returns `Maybe String`, not `String`4. ColumnIndex types need to be converted properlyLet me fix these issues:
</details>

### 💬 Response

I need to fix several type issues. Let me update the module:

### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 37: User Turn



---

## 🤖 Step 38: LLM Turn

### 💭 Thinking Process

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

Now let me try compiling again:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_check-code**

---

## 👤 Step 39: User Turn



---

## 🤖 Step 40: LLM Turn

### 💭 Thinking Process

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

The `columnName` already returns `Maybe Text`, not `Maybe String`. Let me fix that:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_read-file**

---

## 👤 Step 41: User Turn



---

## 🤖 Step 42: LLM Turn

### 💭 Thinking Process

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

I see the issue. The `Direct.columnName` returns `Maybe String`, not `Maybe Text`. But I was checking the type incorrectly. Let me look at the actual error:

```
Expected: String
  Actual: Text
```

Wait, the issue is that the `name` inside `Just name` is already a `String` (which is `[Char]`), but then I'm calling `Text.pack name` on it, expecting to get a `Text` but `Text.pack` expects a `String`... Wait, `Text.pack` does take a `String` and returns `Text`. So that should work.

Actually looking at it again, the error says:
```
• Couldn't match type 'Text' with '[Char]'
  Expected: String
    Actual: Text
```

So `name` is actually `Text` already! This means that `Direct.columnName` returns `Maybe Text`, not `Maybe String`. Let me just use `name` directly:
</details>

### 💬 Response

The `columnName` returns `Maybe Text` already. Let me fix that line:

### 🔧 Tool Calls

- **bash_grep-files**

---

## 👤 Step 43: User Turn



---

## 🤖 Step 44: LLM Turn

### 💭 Thinking Process

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

Let me check the direct-sqlite package to see the actual type signature. Actually, I can just try fixing the line by not using Text.pack.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_write-file**

---

## 👤 Step 45: User Turn



---

## 🤖 Step 46: LLM Turn

### 💭 Thinking Process

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

Now let me try compiling again:
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_check-code**

---

## 👤 Step 47: User Turn



---

## 🤖 Step 48: LLM Turn

### 💭 Thinking Process

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

The code compiles now with just some warnings. The warnings are about unused imports and unused functions, which are not critical. The module is successfully compiled.

Now let me run the tests to make sure everything works:
</details>

### 💬 Response

The module compiles successfully. Now let's run the tests to make sure everything works:

### 🔧 Tool Calls

- **bash_check-code**

---

## 👤 Step 49: User Turn



---

## 🤖 Step 50: LLM Turn

### 💭 Thinking Process

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

All tests pass. The module is now complete. Let me provide a summary of what was created.
</details>

### 💬 Response

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

## Summary

Successfully created the `System.Agents.Tools.SqliteToolbox` module that provides runtime for executing SQL queries against SQLite databases.

### Files Created
- `src/System/Agents/Tools/SqliteToolbox.hs` - The main module implementing SQLite toolbox functionality

### Files Modified
- `agents.cabal` - Added `sqlite-simple` and `direct-sqlite` to library dependencies and exposed the new module

### Key Features Implemented

1. **Core Types**:
   - `Trace` - Events for monitoring operations (connection opened/closed, query started/completed, access violations, errors)
   - `Toolbox` - Runtime state with both sqlite-simple and direct-sqlite connections
   - `QueryResult` - Contains columns, rows as JSON values, row count, and execution time
   - `QueryError` - Error types (SqlError, AccessDeniedError, ConnectionError)

2. **Access Control**:
   - `AccessMode` (ReadOnly | ReadWrite) and `SqlOperation` types
   - `classifyQuery` - Parses SQL to determine operation type (handles comments and whitespace)
   - `allowsOperation` and `validateAccess` - Enforces access control rules

3. **Query Execution**:
   - `initializeToolbox` - Opens database with both connection types, sets up foreign keys
   - `executeQuery` - General-purpose execution respecting configured access mode
   - `executeReadOnlyQuery` - Only allows SELECT queries
   - `executeWriteQuery` - Enforces read-write mode before executing

4. **Result Formatting**:
   - `formatResults` - Returns JSON with columns, rows, rowCount, and executionTime
   - `formatResultsCompact` - Single-line JSON without execution time
   - `formatResultsAsObjects` - Rows as objects instead of arrays
   - Proper SQL to JSON value conversion (integers, floats, text, blobs, null)

The implementation follows the patterns established in other toolbox modules (BashToolbox, PostgRESToolbox, OpenAPIToolbox) and integrates with the existing tracing infrastructure.
