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BytesAgain β€Ί Skills β€Ί Agent Toolkit
πŸ¦€ ClawHub✦ BytesAgain

Agent Toolkit

by @xueyetianya

Configure and benchmark agent tools and integration patterns. Use when setting up agent workflows, comparing tools, or evaluating agents.

Versionv2.0.2
Downloads813
Installs2
#clawhub
TERMINAL
clawhub install agent-toolkit

πŸ“– About This Skill

version: "2.0.1" name: agent-toolkit description: "Configure and benchmark agent tools and integration patterns. Use when setting up agent workflows, comparing tools, or evaluating agents." author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills

Agent Toolkit

A comprehensive AI toolkit for configuring, benchmarking, comparing, and optimizing agent tools and integration patterns. Agent Toolkit 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 tools β€” log configuration entries or view recent ones | | benchmark | Benchmark tool performance β€” log benchmark results or view history | | compare | Compare tool outputs β€” log comparison data or view recent comparisons | | prompt | Prompt management β€” log prompt variations or view recent prompts | | evaluate | Evaluate tool results β€” log evaluation data or view history | | fine-tune | Fine-tune parameters β€” log fine-tuning sessions or view recent ones | | analyze | Analyze tool behavior β€” log analysis entries or view recent analyses | | cost | Cost tracking β€” log cost data or view recent cost entries | | usage | Usage monitoring β€” log usage metrics or view recent usage data | | optimize | Optimize configurations β€” log optimization runs or view history | | test | Test tool behavior β€” log test results or view recent tests | | report | Report generation β€” log report entries or view recent reports | | stats | Show summary statistics across all log categories (entry counts, data size, first entry date) | | export | Export all data in json, csv, or txt format to the data directory | | search | Full-text search across all log files (case-insensitive) | | recent | Show the 20 most recent entries from the activity history log | | status | Health check β€” 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/.log β€” one file per command (e.g., configure.log, benchmark.log, prompt.log), each entry is timestamp|value
  • History log: $DATA_DIR/history.log β€” audit trail of every command executed with timestamps
  • Export files: $DATA_DIR/export. β€” generated by the export command in json, csv, or txt format

    • Default data directory: ~/.local/share/agent-toolkit/

    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. Setting up agent workflows β€” When you need to configure and log settings for agent tool integrations, API connections, or pipeline configurations 2. Benchmarking and comparing tools β€” When you're evaluating different AI tools or agent frameworks and want to log performance metrics for comparison 3. Cost and usage optimization β€” When you need to track API costs, token usage, and resource consumption across different tools to optimize spending 4. Fine-tuning and testing β€” When running fine-tuning experiments or test suites and you want to log parameters, results, and observations 5. Cross-tool analysis and reporting β€” When you need to search across all logged data, generate reports, or export results for stakeholder review

    Examples

    # Check toolkit status
agent-toolkit status
    Configure a new tool integration
    
agent-toolkit configure "OpenAI API key rotated, new model endpoint: gpt-4o-2024-08"
    Benchmark a tool
    
agent-toolkit benchmark "LangChain ReAct agent: 94% task completion, 3.4s avg response time"
    Compare two tools
    
agent-toolkit compare "LangChain vs CrewAI: LangChain 20% faster setup, CrewAI better multi-agent coordination"
    Log a prompt template
    
agent-toolkit prompt "Tool-use system prompt v3: Added structured output format and error handling instructions"
    Track costs
    
agent-toolkit cost "Weekly API spend: OpenAI $12.30, Anthropic $8.50, total $20.80"
    View recent benchmarks
    
agent-toolkit benchmark
    Search across all logs
    
agent-toolkit search "LangChain"
    Export all data as CSV
    
agent-toolkit export csv
    View summary statistics
    
agent-toolkit stats
    Show recent activity
    
agent-toolkit recent

    Output

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

    agent-toolkit export json   # β†’ ~/.local/share/agent-toolkit/export.json
agent-toolkit export csv    # β†’ ~/.local/share/agent-toolkit/export.csv
agent-toolkit export txt    # β†’ ~/.local/share/agent-toolkit/export.txt

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

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    ⚑ When to Use

    TriggerAction
    2. **Benchmarking and comparing tools** β€” When you're evaluating different AI tools or agent frameworks and want to log performance metrics for comparison
    3. **Cost and usage optimization** β€” When you need to track API costs, token usage, and resource consumption across different tools to optimize spending
    4. **Fine-tuning and testing** β€” When running fine-tuning experiments or test suites and you want to log parameters, results, and observations
    5. **Cross-tool analysis and reporting** β€” When you need to search across all logged data, generate reports, or export results for stakeholder review

    πŸ’‘ Examples

    # Check toolkit status
agent-toolkit status
    Configure a new tool integration
    
agent-toolkit configure "OpenAI API key rotated, new model endpoint: gpt-4o-2024-08"
    Benchmark a tool
    
agent-toolkit benchmark "LangChain ReAct agent: 94% task completion, 3.4s avg response time"
    Compare two tools
    
agent-toolkit compare "LangChain vs CrewAI: LangChain 20% faster setup, CrewAI better multi-agent coordination"
    Log a prompt template
    
agent-toolkit prompt "Tool-use system prompt v3: Added structured output format and error handling instructions"
    Track costs
    
agent-toolkit cost "Weekly API spend: OpenAI $12.30, Anthropic $8.50, total $20.80"
    View recent benchmarks
    
agent-toolkit benchmark
    Search across all logs
    
agent-toolkit search "LangChain"
    Export all data as CSV
    
agent-toolkit export csv
    View summary statistics
    
agent-toolkit stats
    Show recent activity
    
agent-toolkit recent