# Conversation a04a8a2eeb18d069c

- Source: `claude`
- User: `pascal`
- System: `Pascals-MBP.local`
- Started: `2026-02-24T17:19:25.414Z`
- CWD: `/Users/pascal/Code/business/convx/.claude/worktrees/agent-a04a8a2e`

## User

_`2026-02-24T17:19:25.414Z`_

In the repo at /Users/pascal/Code/business/convx, create a new file `src/convx_ai/stats.py` that aggregates word counts per day per project from exported session JSON blobs.

## Context

The project exports AI sessions to a `history/` directory. Each session produces a hidden JSON blob file (filename starts with `.`, e.g. `.2026-02-19-1805-some-title.json`) alongside a `.md` file. These JSON blobs serialize `NormalizedSession` objects.

## NormalizedSession structure (from src/convx_ai/models.py)
```python
@dataclass
class NormalizedSession:
    session_key: str
    source_system: str
    session_id: str
    source_path: str
    started_at: str        # ISO 8601 UTC, e.g. "2026-02-19T18:05:59.880000Z"
    user: str
    system_name: str
    cwd: str               # e.g. "/Users/pascal/Code/business/convx"
    messages: list[NormalizedMessage]
    summary: str | None = None
    child_sessions: list | None = None

@dataclass
class NormalizedMessage:
    role: str
    text: str
    timestamp: str | None = None
    kind: str = "user"     # "user" | "assistant" | "system" | "tool"
```

## What to build

### `src/convx_ai/stats.py`

Implement one public function:

```python
def compute_word_series(history_path: Path) -> dict:
    ...
```

It must:
1. Recursively find all files under `history_path` matching `**/.*.json` (hidden JSON blobs — note they start with a dot)
2. For each file, load the JSON and parse `started_at` → date string `"YYYY-MM-DD"`, `cwd` → project name using `Path(cwd).name`
3. Count words: `sum(len(msg["text"].split()) for msg in messages if msg.get("kind") in ("user", "assistant"))`
4. If a session has `child_sessions`, recursively process those too (same date/project attribution — use the child's own `started_at` and `cwd`)
5. Aggregate: accumulate word counts per `(date, project)` pair across all blobs
6. Return a dict with:
   ```python
   {
       "dates":    ["2026-01-01", "2026-01-02", ...],   # sorted ascending, all dates in range (no gaps)
       "projects": ["convx", "other-repo", ...],         # sorted alphabetically
       "series":   {
           "convx":      [0, 142, 0, 88, ...],           # word count per date, 0 if no activity
           "other-repo": [0,   0, 55,  0, ...],
       }
   }
   ```
   Fill gaps: if there are dates with no activity for a project, emit 0 for those dates. Fill the full date range (min date to max date, no gaps).

### Error handling
- Skip files that fail JSON parsing (log a warning to stderr)
- Skip sessions where `started_at` is missing or unparseable
- Skip sessions where `cwd` is empty or missing

### Also add a CLI command in `src/convx_ai/cli.py`

The existing CLI is built with Typer. Add a `stats` command that:
- Takes `--repo` argument (Path, defaults to cwd) 
- Calls `compute_word_series(repo / "history")`
- Prints a simple table to stdout: columns = project names, rows = dates, cells = word counts (skip rows where all projects have 0)

Look at the existing `cli.py` to understand the pattern before editing it.

## Important notes
- The history path to scan is `history/` under the repo root (passed in as `history_path`)
- JSON blobs are hidden files starting with `.` — use `glob("**/.*.json", recursive=True)` or equivalent Path glob
- Use only stdlib + what's already in pyproject.toml (no new dependencies needed for stats.py itself)
- Keep it simple — no classes needed, just functions
- Do not modify any existing files except `cli.py` to add the command

## Agent

_`2026-02-24T17:19:28.204Z`_

I'll create the `stats.py` module and add the CLI command. Let me start by examining the existing code structure to understand the models and CLI patterns.

## Agent

_`2026-02-24T17:19:31.124Z`_

Now let me check a sample JSON blob to understand the actual structure.

## Agent

_`2026-02-24T17:19:36.796Z`_

Perfect. Now I understand the structure. Let me create the `stats.py` module.

## Agent

_`2026-02-24T17:19:58.551Z`_

Now I need to update the CLI to add the word stats command. I noticed there's already a `stats` command in the CLI that shows index totals. I'll rename the new command to `word-stats` to avoid conflicts.

## Agent

_`2026-02-24T17:20:12.684Z`_

Now let me test the implementation to make sure it works correctly.

## Agent

_`2026-02-24T17:20:18.168Z`_

Excellent! The command works. Now let me write some tests for the stats module to ensure it handles edge cases correctly.

## Agent

_`2026-02-24T17:20:22.371Z`_

Now let me create comprehensive tests for the stats module.

## Agent

_`2026-02-24T17:21:00.048Z`_

Now let me run the tests to ensure everything works correctly.

## Agent

_`2026-02-24T17:21:03.532Z`_

Perfect! All tests pass. Now let me verify the CLI command works as expected by testing it again and also checking the help text.

## Agent

_`2026-02-24T17:21:08.906Z`_

Perfect! Let me also run the full test suite to ensure I didn't break anything.

## Agent

_`2026-02-24T17:21:12.647Z`_

Excellent! All tests pass. Let me verify the main CLI help shows the new command.

## Agent

_`2026-02-24T17:21:16.589Z`_

Perfect! Now let me create a sample test with actual data to verify the complete workflow.

## Agent

_`2026-02-24T17:21:19.775Z`_

Let me verify one more edge case - when testing with a repo that has no history directory.

## Agent

_`2026-02-24T17:21:36.712Z`_

Good, error handling works correctly. Now let me write a brief summary of what was created.

## Summary

I've successfully created the word count statistics feature for the convx project. Here's what was implemented:

### Files Created

1. **`/Users/pascal/Code/business/convx/src/convx_ai/stats.py`** - Core statistics module with the following functions:
   - `compute_word_series(history_path)` - Main public function that aggregates word counts per day per project
   - `_parse_date(started_at)` - Parses ISO 8601 timestamps to date strings
   - `_extract_project_name(cwd)` - Extracts project name from cwd path
   - `_count_words(messages)` - Counts words in user and assistant messages only
   - `_process_session(session_data, aggregator)` - Recursively processes sessions and child sessions

2. **`/Users/pascal/Code/business/convx/tests/test_stats.py`** - Comprehensive test suite with 17 tests covering:
   - Date parsing (valid and invalid cases)
   - Project name extraction
   - Word counting logic
   - Session processing with and without children
   - Error handling for malformed JSON
   - Date gap filling
   - Multi-project aggregation
   - Nested directory discovery

### Files Modified

3. **`/Users/pascal/Code/business/convx/src/convx_ai/cli.py`** - Added new CLI command:
   - `convx word-stats` - Displays word count statistics in a formatted table
   - Takes optional `--repo` parameter (defaults to current directory)
   - Skips rows where all projects have 0 activity

### Key Features

- **Recursive processing**: Handles child sessions correctly, attributing them to their own dates/projects
- **Date gap filling**: Ensures continuous date ranges with zeros for days with no activity
- **Error resilience**: Gracefully handles malformed JSON, missing fields, and invalid timestamps
- **Clean functional design**: Pure functions, no classes, well-tested edge cases
- **Zero new dependencies**: Uses only stdlib (json, pathlib, datetime, collections)
- **Rich table output**: Uses Rich library (already a dependency) for formatted table display

### Usage

```bash
# From the project repo
uv run convx word-stats

# Or specify a different repo
uv run convx word-stats --repo /path/to/repo
```

### Test Results

All 44 tests pass (including the 17 new stats tests):

```
tests/test_stats.py - 17/17 PASSED
Full test suite - 44/44 PASSED
```

The implementation follows functional programming principles with pure functions, proper type hints, comprehensive docstrings, and extensive test coverage for all edge cases.
