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

**🔑 Session ID:** 86b22d73-b2a6-4f4f-af76-1b2bb82d4e4f

---

## 📊 Statistics

### Turn Counts

| Metric | Value |
|--------|-------|
| Total Turns | 24 |
| 👤 User Turns | 12 |
| 🤖 LLM Turns | 12 |

### 🔧 Tool Calls

**Total Tool Calls:** 20

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

`bash_create_github_issue`    5 ███████████████████████████

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

`bash_list-files     `    1 █████

`sqlite_knowledge_store_query`    1 █████


### 💾 Byte Usage

`Input     `    188 KiB ████████████████████████████████████████████████████████████

`Output    `      2 KiB 

`Reasoning `      4 KiB █
**Total:** 194 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.
You can call yourself recursively using the architect tool, however each recursive call will incur delay and cost, thus limit these calls to tasks that are worthwile of chunking (e.g., reading and analyzing some web page or document).
The documenter agent can help you navigate the knowledge base.
Your output format may be stored as commit message: hence the first line of your last message should be a summary line.
```

### 💬 User Query

# Properly capture LLM to LLM recursive conversation calls

# IDEA

Today an agent can call other agents (or even itself recursively) with `extraAgents` by running "one-shot" conversation with the original prompt.

We should make agent-via-tool calling clean so that sessions are properly created/saved and tracked in the SessionStore.

Ideally the TUI would show these conversations too, which probably means capturing the proper Traces or adding callbacks in `turnAgentRuntimeIntoIOTool` to capture the sessions and build conversations.

Note: dupe of #347 post #378

---
From #383



### 🛠️ 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_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
- **bash_create_github_issue** (`bash_create_github_issue`)
  - Description: creates a github issue using the 'gh' CLI
- **bash_get_git_log** (`bash_get_git_log`)
  - Description: read a online log of the git history
- **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
- **sqlite_knowledge_store_query** (`sqlite_knowledge_store_query`)
  - Description: A knowledge base about the code base and how it works.
- **io_prompt_agent_architect** (`io_prompt_agent_architect`)
  - Description: asks a prompt to the expert agent: architect
- **io_prompt_agent_documenter** (`io_prompt_agent_documenter`)
  - Description: asks a prompt to the expert agent: documenter

---

## 🤖 Step 2: LLM Turn

### 💭 Thinking Process

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

The user wants me to analyze this feature request and break it down into well-documented GitHub issues following the "Feature Branch Isolation" model. Let me understand what this request is about:

1. Currently, agents can call other agents (or themselves recursively) using `extraAgents` with "one-shot" conversations
2. The goal is to make agent-via-tool calling cleaner so that:
   - Sessions are properly created/saved
   - Sessions are tracked in the SessionStore
   - TUI can show these conversations
   - This probably means capturing proper Traces or adding callbacks in `turnAgentRuntimeIntoIOTool`

Let me first explore the codebase to understand the current structure and then create appropriate issues.
</details>

### 💬 Response

I'll analyze this feature request about capturing LLM-to-LLM recursive conversation calls. Let me first explore the codebase to understand the current implementation.

### 🔧 Tool Calls

- **bash_list-files**

- **sqlite_knowledge_store_query**

- **bash_grep-files**

---

## 👤 Step 3: User Turn



---

## 🤖 Step 4: LLM Turn

### 💭 Thinking Process

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

Good, I found the key files. Let me read the main file `OneShotTool.hs` to understand the current implementation, as well as related files for SessionStore, Conversation, and Trace.
</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>

Let me also look at the Trace types and the Session types to understand how tracing works in the current implementation.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_read-file**

- **bash_read-file**

- **bash_grep-files**

---

## 👤 Step 7: User Turn



---

## 🤖 Step 8: LLM Turn

### 💭 Thinking Process

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

Now let me look at the AgentTree module to understand how extraAgents are wired, and also look at the TUI rendering to understand how conversations are displayed.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_read-file**

- **bash_read-file**

- **bash_read-file**

---

## 👤 Step 9: User Turn



---

## 🤖 Step 10: LLM Turn

### 💭 Thinking Process

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

Now I have a good understanding of the codebase. Let me also check how sessions are currently created and saved, and look at the OS-native persistence layer to understand how conversations are stored.
</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 comprehensive understanding of the codebase. Let me also look at the Session Types to understand the data structures involved.
</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 comprehensive understanding of the codebase. Let me summarize the key points about what needs to be done:

1. **Current Implementation**: `turnAgentRuntimeIntoIOTool` in `OneShotTool.hs` creates "one-shot" agent calls using the original prompt. It:
   - Creates a fresh session with `Session [] <$> newSessionId <*> pure Nothing <*> newTurnId`
   - Generates a new conversation ID with `newConversationId`
   - Uses a no-op tracer: `let tracer = Tracer $ const $ pure ()`
   - Runs the agent and returns the result, but doesn't properly track the session

2. **Problem**: 
   - Sessions are not properly created/saved in the SessionStore
   - The TUI doesn't show these recursive conversations
   - No proper traces are captured for the sub-agent calls
   - The parent-child relationship between conversations is lost

3. **Solution Approach**:
   - Capture proper Traces or add callbacks in `turnAgentRuntimeIntoIOTool`
   - Create/save sessions in the SessionStore
   - Link child sessions to parent conversations via `forkedFromSessionId`
   - Add callbacks to capture the sessions and build conversations
   - Update TUI to show these nested conversations

Now I need to create well-documented GitHub issues following the Feature Branch Isolation model.

Let me think about the chunking strategy:

1. **Issue 1**: Design and implement session tracking infrastructure for agent-to-agent calls
   - Add callbacks/mechanism to capture sub-agent sessions
   - Create parent-child relationship tracking
   - Modify `turnAgentRuntimeIntoIOTool` signature to accept tracking callbacks

2. **Issue 2**: Integrate SessionStore persistence for recursive agent calls
   - Save sub-agent sessions to SessionStore
   - Link child sessions to parent via `forkedFromSessionId`
   - Store conversation lineage information

3. **Issue 3**: Enhance Tracer to capture recursive agent conversations
   - Add new trace types for agent-to-agent calls
   - Wire up tracing in `turnAgentRuntimeIntoIOTool`

4. **Issue 4**: Update TUI to display nested/recursive conversations
   - Show conversation hierarchy
   - Display sub-agent calls within parent conversation

5. **Issue 5**: Final integration and testing
   - End-to-end tests
   - Merge feature branch to main

Let me create these issues now.
</details>

### 💬 Response

Now I have a comprehensive understanding of the codebase. Let me create the well-documented GitHub issues for this feature.

### 🔧 Tool Calls

- **bash_create_github_issue**

---

## 👤 Step 15: User Turn



---

## 🤖 Step 16: LLM Turn

### 💭 Thinking Process

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

Now I need to create the subsequent issues that depend on this one. Let me create issues for SessionStore persistence, Tracer enhancements, TUI updates, and the final merge.
</details>

### 💬 Response



### 🔧 Tool Calls

- **bash_create_github_issue**

---

## 👤 Step 17: User Turn



---

## 🤖 Step 18: LLM Turn

### 💭 Thinking Process

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

Good, now let me create the issue for enhancing the Tracer to capture recursive agent conversations.
</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 TUI update issue and the final merge issue.
</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 final merge issue that will merge the feature branch into main.
</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>

All issues have been created. Let me provide a summary to the user.
</details>

### 💬 Response

I've created a comprehensive set of GitHub issues to implement proper capture of LLM-to-LLM recursive conversation calls. Here's a summary:

## Summary

**Feature Branch:** `gh-384-recursive-agent-calls`

### Issues Created

| Issue | Title | Dependencies |
|-------|-------|--------------|
| #384 | Design session tracking infrastructure for agent-to-agent recursive calls | - |
| #385 | Integrate SessionStore persistence for recursive agent calls | #384 |
| #386 | Enhance Tracer to capture recursive agent conversation traces | #384 |
| #387 | Update TUI to display nested/recursive agent conversations | #385, #386 |
| #388 | Final integration: Merge recursive agent call tracking to main | #387 |

### Key Technical Approach

1. **Session Tracking**: Modified `turnAgentRuntimeIntoIOTool` to accept tracking callbacks and link parent-child sessions via `forkedFromSessionId`

2. **Persistence**: Sub-agent sessions are saved to `SessionStore` during execution, not discarded

3. **Tracing**: Replaced no-op tracer with proper contramapped tracer that captures `AgentTrace_SubAgentCall` events

4. **TUI**: Conversations display hierarchically with expand/collapse for child conversations

### Important Tradeoffs Documented

- **Storage vs Performance**: Each sub-agent call creates a session file (~5-50KB)
- **Synchronous Persistence**: Blocks execution on disk I/O but ensures data integrity
- **Memory Usage**: TUI keeps conversation tree in memory; may need pagination for large trees
- **Depth Limits**: Should respect `defaultMaxToolCallDepth` (10 levels)

### Data Types Reference

Key types used across issues:
```haskell
-- Session parent linkage
data Session = Session
    { forkedFromSessionId :: Maybe SessionId  -- Parent reference
    , ...
    }

-- New trace types
data Trace = ... | AgentTrace_SubAgentCall AgentSlug AgentId ConversationId 
                    AgentSlug ConversationId SubAgentTrace
```

The work is structured to minimize conflicts - each issue modifies different aspects of the codebase while maintaining clean interfaces between components.
