# Claude Code

> Review, validate, and generate code with AI-powered linting. Use when fixing bugs, generating boilerplate, formatting, or running analysis.

- Skill: `bytesagain/claude-code` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add bytesagain/claude-code`
- Raw SKILL.md: https://api.skillmd.com/api/skills/bytesagain/claude-code/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: bytesagain (https://skillmd.com/u/bytesagain)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/bytesagain/claude-code

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# AI Code Helper

A developer tools toolkit for checking, validating, generating, formatting, linting, explaining, converting, and fixing code from the command line. AI Code Helper provides persistent, file-based logging for each operation with timestamped entries, summary statistics, multi-format export, and full-text search across all records.

## Commands

| Command | Description |
|---------|-------------|
| `check` | Check code — log check results or view recent entries |
| `validate` | Validate code or configurations — log validation results or view history |
| `generate` | Generate code snippets or boilerplate — log generation requests or view recent ones |
| `format` | Format code — log formatting operations or view recent entries |
| `lint` | Lint code — log linting results or view recent lint entries |
| `explain` | Explain code — log explanation requests or view recent explanations |
| `convert` | Convert between formats or languages — log conversion operations or view history |
| `template` | Template management — log template operations or view recent templates |
| `diff` | Diff comparison — log diff results or view recent diffs |
| `preview` | Preview changes — log preview operations or view recent previews |
| `fix` | Fix code issues — log fix operations or view recent fixes |
| `report` | Report generation — log report entries or view recent reports |
| `stats` | Show summary statistics across all log categories (entry counts, data size, first entry date) |
| `export <fmt>` | Export all data in json, csv, or txt format to the data directory |
| `search <term>` | Full-text search across all log files (case-insensitive) |
| `recent` | Show the 20 most recent entries from the activity history log |
| `status` | Health check — show version, data directory, total entries, disk usage, and last activity |
| `help` | Show the full help message with all available commands |
| `version` | Print the current version string |

Each data command (check, validate, generate, etc.) works in two modes:
- **Without arguments**: displays the 20 most recent entries from that category
- **With arguments**: saves the input as a new timestamped entry and reports the total count

## Data Storage

All data is stored in plain text files under the data directory:

- **Category logs**: `$DATA_DIR/<command>.log` — one file per command (e.g., `check.log`, `lint.log`, `generate.log`), each entry is `timestamp|value`
- **History log**: `$DATA_DIR/history.log` — audit trail of every command executed with timestamps
- **Export files**: `$DATA_DIR/export.<fmt>` — generated by the `export` command in json, csv, or txt format

Default data directory: `~/.local/share/ai-code-helper/`

## Requirements

- Bash (with `set -euo pipefail` support)
- Standard Unix utilities: `grep`, `cat`, `date`, `echo`, `wc`, `du`, `head`, `tail`, `basename`
- No external dependencies or API keys required

## When to Use

1. **Code review and validation** — When you need to log code review findings, validation results, or quality checks for tracking purposes
2. **Generating boilerplate or snippets** — When you want to log code generation requests and keep a history of what was generated and when
3. **Linting and formatting tracking** — When you're running lint or format passes across a codebase and want to log results for each file or module
4. **Code conversion and migration** — When converting code between languages or formats and you need to track what was converted and any issues found
5. **Bug fixing and diff analysis** — When fixing bugs and you want to log the issue, the fix applied, and preview/diff results for future reference

## Examples

```bash
# Check toolkit status
ai-code-helper status

# Log a code check result
ai-code-helper check "auth.py — missing input validation on login endpoint, 3 issues found"

# Log a validation result
ai-code-helper validate "docker-compose.yml — valid, all services resolve correctly"

# Log a code generation request
ai-code-helper generate "Created REST API boilerplate with FastAPI, includes auth middleware and rate limiting"

# Log a lint pass
ai-code-helper lint "src/ — 12 warnings (unused imports), 0 errors, eslint v8.50"

# Log a code explanation
ai-code-helper explain "Binary search implementation in utils.py — O(log n) time, handles edge cases for empty arrays"

# Log a fix
ai-code-helper fix "Fixed race condition in worker.py — added mutex lock around shared state access"

# View recent lint entries
ai-code-helper lint

# Search across all logs for a specific term
ai-code-helper search "validation"

# Export all data as JSON
ai-code-helper export json

# View summary statistics
ai-code-helper stats

# Show recent activity
ai-code-helper recent
```

## Output

All commands return output to stdout. Export files are written to the data directory:

```bash
ai-code-helper export json   # → ~/.local/share/ai-code-helper/export.json
ai-code-helper export csv    # → ~/.local/share/ai-code-helper/export.csv
ai-code-helper export txt    # → ~/.local/share/ai-code-helper/export.txt
```

Every command execution is logged to `$DATA_DIR/history.log` for auditing purposes.

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