Agent Learner

---
version: "2.0.1"
name: agent-learner
description: "Benchmark and compare agent prompts and evaluation results. Use when tuning strategies, evaluating outputs, or comparing configurations."
author: BytesAgain
homepage: https://bytesagain.com
source: https://github.com/bytesagain/ai-skills
---

# Agent Learner

An AI toolkit for configuring, benchmarking, comparing, and optimizing agent prompts and evaluation results. Agent Learner provides persistent, file-based logging for each command category with timestamped entries, summary statistics, multi-format export, and full-text search across all records.

## Commands

| Command | Description |
|---------|-------------|
| `configure` | Configure agent settings — log configuration entries or view recent ones |
| `benchmark` | Benchmark agent performance — log benchmark results or view history |
| `compare` | Compare agent outputs — log comparison data or view recent comparisons |
| `prompt` | Prompt management — log prompt variations or view recent prompts |
| `evaluate` | Evaluate agent outputs — log evaluation results or view history |
| `fine-tune` | Fine-tune parameters — log fine-tuning sessions or view recent ones |
| `analyze` | Analyze agent behavior — log analysis entries or view recent analyses |
| `cost` | Cost tracking — log cost data or view recent cost entries |
| `usage` | Usage monitoring — log usage metrics or view recent usage data |
| `optimize` | Optimize configurations — log optimization runs or view history |
| `test` | Test agent behavior — log test results or view recent tests |
| `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 (configure, benchmark, compare, 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**: `$DATA_DIR/<command>.log` — one file per command (e.g., `configure.log`, `benchmark.log`, `prompt.log`), each entry is `timestamp|value`
- **History log**: `$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/agent-learner/`

## 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. **Benchmarking agent performance** — When you need to track and compare benchmark results across different agent configurations, models, or prompt strategies
2. **Prompt engineering iteration** — When you're testing multiple prompt variations and want to log each version with results for later comparison
3. **Cost and usage tracking** — When you need to monitor API costs and usage metrics over time to optimize spending
4. **Fine-tuning experiments** — When running fine-tuning sessions and you want to log parameters, results, and observations for reproducibility
5. **Cross-category analysis** — When you need to search across all logged data (benchmarks, prompts, evaluations, costs) to find patterns or specific entries

## Examples

```bash
# Initialize and check status
agent-learner status

# Log a benchmark result
agent-learner benchmark "GPT-4o on MMLU: 88.7% accuracy, 1.2s avg latency"

# Log a prompt variation
agent-learner prompt "System: You are a helpful coding assistant. Always explain your reasoning step by step."

# Compare two configurations
agent-learner compare "GPT-4o vs Claude-3.5: GPT-4o 12% faster, Claude 5% more accurate on code tasks"

# Track costs
agent-learner cost "March batch: 12,450 tokens input, 3,200 tokens output, $0.47 total"

# View all recent benchmarks
agent-learner benchmark

# Search across all logs for a specific term
agent-learner search "accuracy"

# Export all data as JSON
agent-learner export json

# View summary statistics
agent-learner stats

# Show recent activity
agent-learner recent
```

## Output

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

```bash
agent-learner export json   # → ~/.local/share/agent-learner/export.json
agent-learner export csv    # → ~/.local/share/agent-learner/export.csv
agent-learner export txt    # → ~/.local/share/agent-learner/export.txt
```

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

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