TASK-O-MATIC

TECHNICAL BULLETIN NO. 005

BENCHMARK COMMANDS - PERFORMANCE ANALYSIS FIELD OPERATIONS

DOCUMENT ID: task-o-matic-cli-benchmark-commands-v1

CLEARANCE: All Personnel

MANDATORY COMPLIANCE: Yes

⚠️ CRITICAL SURVIVAL NOTICE

Citizen, benchmark commands are your intelligence gathering tools in the post-deadline wasteland. Without proper performance analysis, you're flying blind into AI provider selection storms. These commands provide the data needed to make informed decisions about which AI models and tools will keep your projects alive.

COMMAND ARCHITECTURE OVERVIEW

The benchmark command group represents the performance analysis and optimization layer of Task-O-Matic. It provides comprehensive testing capabilities across multiple AI providers, models, and workflows. The architecture supports concurrent testing, progressive model escalation, and detailed performance metrics collection.

Performance Analysis Components:

Multi-Provider Testing: Compare performance across OpenRouter, Anthropic, OpenAI, and custom endpoints
Model Benchmarking: Detailed performance metrics for individual AI models
Workflow Analysis: End-to-end workflow performance across complete project lifecycles
Progressive Escalation: Automatic retry with better models on failure
Comprehensive Metrics: Latency, throughput, cost, and quality measurements

COMPLETE BENCHMARK COMMAND DOCUMENTATION

RUN COMMAND

Command: task-o-matic benchmark run

COMMAND SIGNATURE

task-o-matic benchmark run <operation> --models <list> [options]

REQUIRED ARGUMENTS

<operation>                  # Operation to benchmark (prd-parse, task-breakdown, task-create, prd-create, etc.)
<models>                    # Comma-separated list of models (required)

REQUIRED OPTIONS

--models <list>              # Comma-separated list of models (provider:model[:reasoning=<tokens>])

GENERAL OPTIONS

--file <path>                # Input file path (for PRD ops)
--task-id <id>               # Task ID (for Task ops)
--concurrency <number>        # Max concurrent requests (default: 5)
--delay <number>               # Delay between requests in ms (default: 250)
--prompt <prompt>             # Override prompt
--message <message>           # User message
--tools                      # Enable filesystem tools
--feedback <feedback>         # Feedback (for prd-rework)

TASK CREATION OPTIONS

--title <title>              # Task title (for task-create)
--content <content>           # Task content (for task-create)
--parent-id <id>             # Parent task ID (for task-create)
--effort <effort>            # Effort estimate: small, medium, large (for task-create)
--force                      # Force operation (for task-document)

PRD CREATION OPTIONS

--description <desc>          # Project/PRD description (for prd-create, prd-combine)
--output-dir <dir>           # Output directory (for prd-create, prd-combine)
--filename <name>            # Output filename (for prd-create, prd-combine)

PRD PROCESSING OPTIONS

--prds <list>                # Comma-separated list of PRD file paths (for prd-combine)

PRD REFINEMENT OPTIONS

--question-mode <mode>        # Question mode: user or ai (for prd-refine)
--answers <json>              # JSON string of answers (for prd-refine user mode)

BENCHMARK RUN EXAMPLES

#### Basic Benchmarking

# Simple PRD parsing benchmark
task-o-matic benchmark run prd-parse \
  --models "anthropic:claude-3.5-sonnet,openai:gpt-4"

# Task creation benchmark
task-o-matic benchmark run task-create \
  --models "openrouter:anthropic/claude-3.5-sonnet,openrouter:openai/gpt-4o" \
  --title "Build radiation detector" \
  --content "Implement Geiger counter integration" \
  --effort medium

# PRD creation benchmark
task-o-matic benchmark run prd-create \
  --models "anthropic:claude-3.5-sonnet,openai:gpt-4,google:gemini-pro" \
  --description "Emergency shelter management system"

#### Advanced Benchmarking with Reasoning

# Benchmark with reasoning tokens
task-o-matic benchmark run task-breakdown \
  --models "openrouter:anthropic/claude-3.5-sonnet:reasoning=2048,openrouter:openai/o1-preview:reasoning=8192" \
  --task-id task-complex-123 \
  --tools

# Multi-model PRD generation with reasoning
task-o-matic benchmark run prd-create \
  --models "anthropic:claude-opus-2024:reasoning=4096,openrouter:anthropic/claude-3.5-sonnet:reasoning=2048" \
  --description "AI-powered emergency response system"

# Task enhancement with reasoning
task-o-matic benchmark run task-enhance \
  --models "openrouter:anthropic/claude-3.5-sonnet:reasoning=1024" \
  --task-id task-123 \
  --tools

#### Workflow Benchmarking

# Complete workflow benchmark
task-o-matic benchmark run workflow-full \
  --models "anthropic:claude-3.5-sonnet,openai:gpt-4" \
  --project-name "Wasteland Shelter" \
  --init-method ai \
  --project-description "Emergency shelter management system"

# Multi-step workflow benchmark
task-o-matic benchmark run workflow-full \
  --models "openrouter:anthropic/claude-3.5-sonnet,openrouter:openai/gpt-4o,openrouter:google/gemini-2.0-flash-exp" \
  --auto-accept \
  --skip-refine \
  --generate-method ai \
  --split-all

#### Custom Operation Benchmarking

# PRD rework benchmark
task-o-matic benchmark run prd-rework \
  --models "anthropic:claude-3.5-sonnet,openai:gpt-4" \
  --file ./requirements.md \
  --feedback "Add more security requirements and technical specifications"

# PRD question generation benchmark
task-o-matic benchmark run prd-question \
  --models "openrouter:anthropic/claude-3.5-sonnet,openai:gpt-4" \
  --file ./prd.md \
  --tools

# PRD refine benchmark
task-o-matic benchmark run prd-refine \
  --models "anthropic:claude-3.5-sonnet,openai:gpt-4" \
  --question-mode ai \
  --file ./prd.md

MODEL FORMAT SPECIFICATIONS

#### Basic Model Format

provider:model

#### Model Format Examples

# Anthropic models
anthropic:claude-3.5-sonnet
anthropic:claude-opus-2024

# OpenAI models
openai:gpt-4
openai:gpt-4-turbo
openai:o1-preview

# OpenRouter models
openrouter:anthropic/claude-3.5-sonnet
openrouter:openai/gpt-4o
openrouter:google/gemini-2.0-flash-exp

# Custom endpoints
custom:http://localhost:8080/v1/custom-model

#### Advanced Model Format with Reasoning

provider:model:reasoning=<tokens>

#### Reasoning Examples

# OpenRouter with reasoning
openrouter:anthropic/claude-3.5-sonnet:reasoning=2048
openrouter:openai/o1-preview:reasoning=8192
openrouter:google/gemini-2.0-flash-exp:reasoning=4096

# OpenAI with reasoning (if supported)
openai:o1-preview:reasoning=4096

BENCHMARK RUN OUTPUT FORMAT

#### Real-time Progress Display

Benchmark Progress:
- anthropic:claude-3.5-sonnet: Starting...
- openai:gpt-4: Running... Size: 2048 B, Speed: 15.2 B/s
- anthropic:claude-3.5-sonnet: Completed (2340ms)
- openai:gpt-4: Completed (3120ms)

#### Final Results Table

Model                                     | Duration | TTFT    | Tokens   | TPS     | BPS     | Size     | Cost
-------------------------------------------|----------|----------|----------|---------|---------|----------|----------
anthropic:claude-3.5-sonnet                | 2340ms   | 120ms    | 1250     | 0.53    | 89      | 208      | $0.004250
openai:gpt-4                              | 3120ms   | 180ms    | 980      | 0.31    | 67      | 195      | $0.039200
openrouter:anthropic/claude-3.5-sonnet     | 2450ms   | 135ms    | 1180     | 0.48    | 85      | 202      | $0.004720

PERFORMANCE METRICS

#### Measured Metrics

Duration: Total execution time in milliseconds
TTFT (Time to First Token): Response latency measurement
Tokens: Total token usage (prompt + completion)
TPS (Tokens Per Second): Processing speed measurement
BPS (Bytes Per Second): Data transfer rate
Response Size: Output size in bytes
Cost: Estimated API cost in USD

#### Metric Calculations

# TPS Calculation
TPS = Total Tokens / (Duration / 1000)

# BPS Calculation  
BPS = Response Size / (Duration / 1000)

# Cost Estimation
Cost = (Prompt Tokens * Prompt Rate) + (Completion Tokens * Completion Rate)

ERROR CONDITIONS

# Invalid model format
Error: Invalid model format: invalid-model. Expected provider:model[:reasoning=<tokens>]
Solution: Use format "provider:model" or "provider:model:reasoning=tokens"

# Operation not found
Error: Benchmark operation 'invalid-op' not found
Solution: Use 'benchmark operations' to see available operations

# Concurrency limit exceeded
Error: Too many concurrent requests
Solution: Reduce --concurrency value or increase --delay

# Rate limiting
Error: Rate limit exceeded for provider
Solution: Increase --delay between requests

LIST COMMAND

Command: task-o-matic benchmark list

COMMAND SIGNATURE

task-o-matic benchmark list

LIST COMMAND EXAMPLES

#### Basic Listing

# List all benchmark runs
task-o-matic benchmark list

# List with details
task-o-matic benchmark list --verbose

LIST OUTPUT FORMAT

#### Standard Output

Benchmark Runs:
- 2024-01-15_14-30-22_prd-parse (2024-01-15 2:30:22 PM) - prd-parse
- 2024-01-15_13-45-10_task-create (2024-01-15 1:45:10 PM) - task-create
- 2024-01-14_16-20-45_workflow-full (2024-01-14 4:20:45 PM) - workflow-full

#### Detailed Output with Metadata

Benchmark Runs:
ID: 2024-01-15_14-30-22_prd-parse
Date: 2024-01-15 2:30:22 PM
Operation: prd-parse
Models: anthropic:claude-3.5-sonnet, openai:gpt-4
Duration: 5460ms
Success Rate: 100%
Average TTFT: 145ms
Total Tokens: 2450
Estimated Cost: $0.043650

ID: 2024-01-15_13-45-10_task-create
Date: 2024-01-15 1:45:10 PM
Operation: task-create
Models: openrouter:anthropic/claude-3.5-sonnet
Duration: 2340ms
Success Rate: 100%
Average TTFT: 120ms
Total Tokens: 1250
Estimated Cost: $0.004250

BENCHMARK HISTORY ANALYSIS

#### Performance Trends

Model Comparison: Compare performance across different runs
Temporal Analysis: Identify performance changes over time
Cost Tracking: Monitor API usage costs
Success Rates: Track reliability and consistency

#### Run Filtering

# Filter by operation type
task-o-matic benchmark list | grep prd-parse

# Filter by date range
task-o-matic benchmark list | grep "2024-01-1"

# Filter by model
task-o-matic benchmark list | grep "claude-3.5-sonnet"

OPERATIONS COMMAND

Command: task-o-matic benchmark operations

COMMAND SIGNATURE

task-o-matic benchmark operations

OPERATIONS COMMAND EXAMPLES

#### Basic Operations Listing

# List all available operations
task-o-matic benchmark operations

# List with categories
task-o-matic benchmark operations --categorized

OPERATIONS OUTPUT FORMAT

#### Categorized Operations List

📊 Available Benchmark Operations

Task Operations:
  task-create          - Create a new task with AI enhancement
  task-enhance        - Enhance an existing task with AI
  task-breakdown      - Break task into subtasks using AI
  task-document       - Fetch and analyze documentation for task

PRD Operations:
  prd-create          - Generate PRD from product description
  prd-parse           - Parse PRD into structured tasks
  prd-rework          - Rework PRD based on feedback
  prd-combine         - Combine multiple PRDs into master PRD
  prd-question        - Generate clarifying questions for PRD
  prd-refine          - Refine PRD by answering questions

Workflow Operations:
  workflow-full       - Complete workflow execution
  workflow-init       - Project initialization step
  workflow-prd        - PRD creation and refinement
  workflow-generate   - Task generation from PRD
  workflow-split      - Task splitting into subtasks

Total operations: 14

#### Operation Details

# Get details for specific operation
task-o-matic benchmark operations --details task-create

# Search operations by keyword
task-o-matic benchmark operations --search "enhance"

# Filter by category
task-o-matic benchmark operations --category task

OPERATION CATEGORIES

#### Task Operations

Creation: AI-powered task generation and enhancement
Enhancement: Task description improvement with Context7
Breakdown: Intelligent task decomposition into subtasks
Documentation: Automatic documentation research and integration

#### PRD Operations

Generation: AI-powered PRD creation from descriptions
Parsing: Structured task extraction from PRD documents
Refinement: PRD improvement through feedback and Q&A
Combination: Multiple PRD synthesis into master documents

#### Workflow Operations

End-to-End: Complete project lifecycle benchmarking
Step Analysis: Individual workflow component performance
Integration: Cross-component performance measurement

SHOW COMMAND

Command: task-o-matic benchmark show

COMMAND SIGNATURE

task-o-matic benchmark show <id>

REQUIRED ARGUMENTS

<id>                        # Run ID to display details for (required)

SHOW COMMAND EXAMPLES

#### Basic Run Display

# Show benchmark run details
task-o-matic benchmark show 2024-01-15_14-30-22_prd-parse

# Show workflow benchmark details
task-o-matic benchmark show 2024-01-14_16-20-45_workflow-full

#### Detailed Analysis Examples

# Show run with full configuration
task-o-matic benchmark show 2024-01-15_13-45-10_task-create --verbose

# Show specific model results
task-o-matic benchmark show 2024-01-15_14-30-22_prd-parse --model anthropic:claude-3.5-sonnet

# Show error analysis
task-o-matic benchmark show 2024-01-15_11-30-15_prd-parse --errors

SHOW OUTPUT FORMAT

#### Standard Run Display

Run: 2024-01-15_14-30-22_prd-parse
Date: 2024-01-15 2:30:22 PM
Operation: prd-parse
Configuration:
  Concurrency: 5
  Delay: 250ms
  Models: anthropic:claude-3.5-sonnet, openai:gpt-4

Input:
  File: ./requirements.md
  Prompt: Default PRD parsing prompt
  Message: Parse PRD into structured tasks

Results:
 anthropropic:claude-3.5-sonnet:
   Duration: 2340ms
   TTFT: 120ms
   Tokens: 1250 (Prompt: 800, Completion: 450)
   TPS: 0.53
   BPS: 89
   Size: 208 bytes
   Cost: $0.004250
   Status: Success

 openai:gpt-4:
   Duration: 3120ms
   TTFT: 180ms
   Tokens: 980 (Prompt: 750, Completion: 230)
   TPS: 0.31
   BPS: 67
   Size: 195 bytes
   Cost: $0.039200
   Status: Success

Summary:
 Total Duration: 5460ms
 Average TTFT: 150ms
 Total Tokens: 2230
 Total Cost: $0.083450
 Success Rate: 100%

#### Error Analysis Display

# Show run with error details
task-o-matic benchmark show 2024-01-15_11-30-15_prd-parse --errors

# Show specific model errors
task-o-matic benchmark show 2024-01-15_14-30-22_prd-parse --model-errors

COMPARE COMMAND

Command: task-o-matic benchmark compare

COMMAND SIGNATURE

task-o-matic benchmark compare <id>

REQUIRED ARGUMENTS

<id>                        # Run ID to compare results for (required)

COMPARE COMMAND EXAMPLES

#### Basic Comparison

# Compare benchmark run results
task-o-matic benchmark compare 2024-01-15_14-30-22_prd-parse

# Compare workflow benchmark
task-o-matic benchmark compare 2024-01-14_16-20-45_workflow-full

#### Advanced Comparison Analysis

# Compare with detailed metrics
task-o-matic benchmark compare 2024-01-15_13-45-10_task-create --detailed

# Compare specific models
task-o-matic benchmark compare 2024-01-15_14-30-22_prd-parse --models anthropic:claude-3.5-sonnet,openai:gpt-4

COMPARE OUTPUT FORMAT

#### Comparison Table

Comparison for Run: 2024-01-15_14-30-22_prd-parse

Model                    | Status | Duration | Tokens | Cost   | Efficiency
------------------------|--------|----------|---------|-----------|----------
anthropic:claude-3.5-sonnet | SUCCESS | 2340ms   | 1250    | $0.004250 | 0.53 TPS
openai:gpt-4             | SUCCESS | 3120ms   | 980     | $0.039200 | 0.31 TPS

Performance Analysis:
- Fastest Model: anthropic:claude-3.5-sonnet (2340ms)
- Most Cost-Effective: anthropic:claude-3.5-sonnet ($0.004250)
- Highest Throughput: anthropic:claude-3.5-sonnet (0.53 TPS)
- Best Value: anthropic:claude-3.5-sonnet (Speed + Cost balance)

#### Statistical Analysis

# Performance distribution
Duration: Mean=2730ms, Median=2340ms, Min=2340ms, Max=3120ms
Tokens: Mean=1115, Median=1250, Min=980, Max=1250
Cost: Mean=$0.041725, Median=$0.004250, Min=$0.004250, Max=$0.039200

Success Rate: 100% (2/2 models successful)
Error Rate: 0% (0/2 models failed)

WORKFLOW COMMAND

Command: task-o-matic benchmark workflow

COMMAND SIGNATURE

task-o-matic benchmark workflow --models <list> [options]

REQUIRED OPTIONS

--models <list>              # Comma-separated list of models (required)

WORKFLOW CONFIGURATION OPTIONS

--concurrency <number>        # Max concurrent requests (default: 3)
--delay <number>             # Delay between requests in ms (default: 1000)
--stream                     # Show streaming AI output
--skip-all                   # Skip all optional steps (use defaults)
--auto-accept                # Auto-accept all AI suggestions
--config-file <path>         # Load workflow options from JSON file

WORKFLOW STEP OPTIONS

#### Initialization Options

--skip-init                 # Skip initialization step
--project-name <name>        # Project name
--init-method <method>       # Initialization method: quick, custom, ai
--project-description <desc>  # Project description for AI-assisted init
--use-existing-config       # Use existing configuration if found
--frontend <framework>        # Frontend framework
--backend <framework>         # Backend framework
--database <db>             # Database choice
--auth                       # Include authentication
--no-auth                     # Exclude authentication
--bootstrap                   # Bootstrap with Better-T-Stack
--no-bootstrap               # Skip bootstrapping

#### PRD Definition Options

--skip-prd                  # Skip PRD definition
--prd-method <method>        # PRD method: upload, manual, ai, skip
--prd-file <path>           # Path to existing PRD file
--prd-description <desc>    # Product description for AI-assisted PRD
--prd-content <content>       # Direct PRD content

#### PRD Refinement Options

--skip-refine               # Skip PRD refinement
--refine-method <method>     # Refinement method: manual, ai, skip
--refine-feedback <feedback> # Feedback for AI refinement

#### Task Generation Options

--skip-generate             # Skip task generation
--generate-method <method>   # Generation method: standard, ai
--generate-instructions <instructions> # Custom task generation instructions

#### Task Splitting Options

--skip-split                # Skip task splitting
--split-tasks <ids>         # Comma-separated task IDs to split
--split-all                  # Split all tasks
--split-method <method>      # Split method: interactive, standard, custom
--split-instructions <instructions> # Custom split instructions

WORKFLOW BENCHMARK EXAMPLES

#### Basic Workflow Benchmark

# Simple workflow benchmark
task-o-matic benchmark workflow \
  --models "anthropic:claude-3.5-sonnet,openai:gpt-4"

# Workflow with custom settings
task-o-matic benchmark workflow \
  --models "openrouter:anthropic/claude-3.5-sonnet,openrouter:openai/gpt-4o" \
  --concurrency 2 \
  --delay 2000 \
  --auto-accept

# Workflow with specific steps
task-o-matic benchmark workflow \
  --models "anthropic:claude-3.5-sonnet" \
  --project-name "Wasteland Shelter" \
  --init-method ai \
  --project-description "Emergency shelter management" \
  --skip-refine \
  --generate-method ai \
  --split-all

#### Advanced Workflow Scenarios

# Multi-model workflow with reasoning
task-o-matic benchmark workflow \
  --models "anthropic:claude-opus-2024:reasoning=4096,openrouter:anthropic/claude-3.5-sonnet:reasoning=2048,openrouter:openai/o1-preview:reasoning=8192" \
  --concurrency 1 \
  --delay 5000

# Workflow from configuration file
task-o-matic benchmark workflow \
  --models "anthropic:claude-3.5-sonnet,openai:gpt-4" \
  --config-file ./workflow-config.json

# Workflow with selective steps
task-o-matic benchmark workflow \
  --models "openrouter:anthropic/claude-3.5-sonnet" \
  --skip-init \
  --prd-method upload \
  --prd-file ./existing-prd.md \
  --generate-method standard \
  --split-tasks "task-123,task-456"

WORKFLOW BENCHMARK OUTPUT

#### Real-time Progress

🚀 Task-O-Matic Workflow Benchmark

Models: 3, Concurrency: 2, Delay: 2000ms

- anthropic:claude-opus-2024:reasoning=4096: Starting...
- openrouter:anthropic/claude-3.5-sonnet: Starting...
- openrouter:openai/gpt-4o: Starting...

Step 1: Initialize
- anthropic:claude-opus-2024:reasoning=4096: Running... Project setup
- openrouter:anthropic/claude-3.5-sonnet: Running... Project setup
- openrouter:openai/gpt-4o: Running... Project setup

Step 2: Define PRD
- anthropic:claude-opus-2024:reasoning=4096: Completed (5430ms)
- openrouter:anthropic/claude-3.5-sonnet: Completed (6120ms)
- openrouter:openai/gpt-4o: Completed (7890ms)

Step 3: Refine PRD
- anthropic:claude-opus-2024:reasoning=4096: Skipped
- openrouter:anthropic/claude-3.5-sonnet: Skipped
- openrouter:openai/gpt-4o: Skipped

Step 4: Generate Tasks
- anthropic:claude-opus-2024:reasoning=4096: Running... Task generation
- openrouter:anthropic/claude-3.5-sonnet: Running... Task generation
- openrouter:openai/gpt-4o: Running... Task generation

Step 5: Split Tasks
- anthropic:claude-opus-2024:reasoning=4096: Running... Task splitting
- openrouter:anthropic/claude-3.5-sonnet: Running... Task splitting
- openrouter:openai/gpt-4o: Running... Task splitting

#### Final Results Summary

✅ Workflow benchmark completed! Run ID: 2024-01-15_14-30-22_workflow-full

📊 Workflow Benchmark Results

Model                               | Duration | Tasks | PRD Size | Steps | Cost
-----------------------------------|----------|--------|----------|-------|--------
anthropic:claude-opus-2024:reasoning=4096 | 15420ms  | 12     | 2.1KB  | 5/5   | $0.156
openrouter:anthropic/claude-3.5-sonnet     | 18930ms  | 10     | 1.8KB  | 5/5   | $0.089
openrouter:openai/gpt-4o               | 22150ms  | 8      | 1.6KB  | 5/5   | $0.124

Performance Analysis:
- Fastest Overall: openrouter:anthropic/claude-3.5-sonnet (18930ms)
- Best Task Generation: anthropic:claude-opus-2024 (12 tasks)
- Most Cost-Effective: openrouter:anthropic/claude-3.5-sonnet ($0.089)
- Highest Quality: anthropic:claude-opus-2024 (5/5 steps completed)

WORKFLOW PERFORMANCE METRICS

#### Workflow Step Analysis

Initialization Time: Project setup and configuration
PRD Generation Time: PRD creation and processing
Task Generation Time: Task extraction from PRD
Task Splitting Time: Task decomposition into subtasks
Total Workflow Time: End-to-end completion time

#### Quality Assessment

Step Completion Rate: Percentage of workflow steps completed successfully
Task Quality: Number and quality of generated tasks
PRD Coherence: Logical consistency and completeness
Integration Success: How well components work together

#### Cost Analysis

Per-Step Costs: Individual cost breakdown for each workflow step
Total Cost: Aggregate cost across entire workflow
Cost Efficiency: Cost per task or per workflow step
ROI Analysis: Cost vs. output quality relationship

ERROR CONDITIONS

# Invalid model format in workflow
Error: Invalid model format: invalid-model. Expected provider:model[:reasoning=<tokens>]
Solution: Use correct format for all models in workflow

# Concurrency too high for workflow
Error: Workflow concurrency too high for system resources
Solution: Reduce --concurrency or increase system resources

# Workflow step failure
Error: Workflow step 'initialize' failed for model anthropic:claude-3.5-sonnet
Solution: Check model configuration and retry with different model

# Partial workflow completion
Warning: Some workflow steps failed for certain models
Solution: Review individual step results and adjust configuration

FIELD OPERATIONS PROTOCOLS

#### BENCHMARK LIFECYCLE MANAGEMENT

The benchmark commands implement a complete performance testing lifecycle:

Test Planning Phase

- Operation selection and parameter configuration

- Model selection and format validation

- Concurrency and delay optimization

- Test data and input preparation

Execution Phase

- Concurrent model execution with rate limiting

- Real-time progress tracking and status updates

- Error handling and retry logic

- Performance metrics collection

Analysis Phase

- Result aggregation and statistical analysis

- Performance comparison and ranking

- Cost analysis and optimization recommendations

- Error pattern identification and reporting

Reporting Phase

- Detailed result display with multiple format options

- Historical trend analysis and comparison

- Export capabilities for external analysis

- Visual performance charts and graphs

#### PERFORMANCE OPTIMIZATION STRATEGIES

All benchmark operations support performance optimization through:

Model Selection: Data-driven model recommendations based on historical performance
Parameter Tuning: Automatic optimization of concurrency and delay settings
Cost Management: Real-time cost tracking and budget enforcement
Quality Balancing: Trade-off analysis between speed, cost, and quality
Resource Efficiency: Optimal utilization of system resources

#### INTEGRATION PATTERNS

Benchmark operations integrate with other Task-O-Matic components:

Service Integration: Direct calls to TaskService, PRDService, WorkflowService
Configuration Management: Unified configuration system across all operations
Storage Integration: Results storage in .task-o-matic/benchmark/ directory
AI Provider Abstraction: Consistent interface across all supported AI providers
Error Handling: Standardized error reporting and recovery mechanisms

SURVIVAL SCENARIOS

#### SCENARIO 1: AI Model Selection for Project Setup

# Benchmark PRD parsing models
task-o-matic benchmark run prd-parse \
  --models "anthropic:claude-3.5-sonnet,openai:gpt-4,openrouter:anthropic/claude-3.5-sonnet,openrouter:openai/gpt-4o,google:gemini-pro" \
  --file ./project-requirements.md

# Analyze results for model selection
task-o-matic benchmark show 2024-01-15_14-30-22_prd-parse

# Compare cost-effectiveness
task-o-matic benchmark compare 2024-01-15_14-30-22_prd-parse --metric cost-per-token

# Select best performing model
# Based on results: anthropic:claude-3.5-sonnet showed best balance of speed and cost

#### SCENARIO 2: Workflow Performance Optimization

# Benchmark complete workflow
task-o-matic benchmark workflow \
  --models "anthropic:claude-3.5-sonnet,openai:gpt-4" \
  --project-name "Performance Test" \
  --auto-accept

# Test different concurrency settings
task-o-matic benchmark workflow \
  --models "openrouter:anthropic/claude-3.5-sonnet" \
  --concurrency 1 \
  --project-name "Concurrency Test 1"

task-o-matic benchmark workflow \
  --models "openrouter:anthropic/claude-3.5-sonnet" \
  --concurrency 3 \
  --project-name "Concurrency Test 3"

task-o-matic benchmark workflow \
  --models "openrouter:anthropic/claude-3.5-sonnet" \
  --concurrency 5 \
  --project-name "Concurrency Test 5"

# Analyze optimal concurrency
task-o-matic benchmark compare 2024-01-15_14-30-22_workflow-full \
  --compare-with 2024-01-15_14-30-22_workflow-full_concurrency-1 \
  --compare-with 2024-01-15_14-30-22_workflow-full_concurrency-3 \
  --compare-with 2024-01-15_14-30-22_workflow-full_concurrency-5

#### SCENARIO 3: Cost Management and Budgeting

# Benchmark with cost tracking
task-o-matic benchmark run task-create \
  --models "openrouter:anthropic/claude-3.5-sonnet,openrouter:openai/gpt-4o" \
  --title "Cost analysis task" \
  --budget 0.10

# Monitor cost over time
task-o-matic benchmark list | grep "Cost analysis"
task-o-matic benchmark show --cost-analysis

# Compare cost efficiency
task-o-matic benchmark compare cost-analysis-run-1 cost-analysis-run-2

# Set cost alerts
task-o-matic benchmark run task-create \
  --models "openrouter:anthropic/claude-3.5-sonnet" \
  --cost-alert 0.05

#### SCENARIO 4: Quality Assurance and Testing

# Benchmark for quality metrics
task-o-matic benchmark run prd-parse \
  --models "anthropic:claude-3.5-sonnet,openai:gpt-4" \
  --quality-metrics accuracy,coherence,completeness

# Test with different prompts
task-o-matic benchmark run prd-parse \
  --models "openrouter:anthropic/claude-3.5-sonnet" \
  --prompt "Detailed technical analysis required" \
  --prompt "Quick overview needed" \
  --prompt "Focus on security requirements"

# Compare prompt effectiveness
task-o-matic benchmark compare prompt-test-run-1 prompt-test-run-2

# Quality scoring analysis
task-o-matic benchmark show prompt-test-run-1 --quality-scores

TECHNICAL SPECIFICATIONS

#### BENCHMARK DATA MODEL

interface BenchmarkRun {
  id: string;                    // Unique run identifier
  timestamp: Date;               // When benchmark was executed
  operation: string;              // Type of operation benchmarked
  config: {                     // Benchmark configuration
    models: BenchmarkModelConfig[];
    concurrency: number;
    delay: number;
  };
  input: any;                     // Input parameters for benchmark
  results: BenchmarkResult[];    // Results for each model
}

interface BenchmarkResult {
  modelId: string;               // Model identifier (provider:model)
  duration: number;              // Execution time in milliseconds
  timeToFirstToken?: number;    // TTFT in milliseconds
  tokenUsage?: {                // Token usage breakdown
    prompt: number;
    completion: number;
    total: number;
  };
  tps?: number;                 // Tokens per second
  bps?: number;                 // Bytes per second
  responseSize?: number;          // Response size in bytes
  cost?: number;                 // Estimated cost in USD
  output?: any;                 // Operation output
  error?: string;                // Error message if failed
}

interface BenchmarkModelConfig {
  provider: string;              // AI provider name
  model: string;                // Model name
  reasoningTokens?: number;       // Reasoning token limit (if applicable)
}

#### PERFORMANCE CHARACTERISTICS

Concurrent Execution: Support for multiple simultaneous model tests
Rate Limiting: Configurable delays between requests
Progress Tracking: Real-time status updates during execution
Error Recovery: Automatic retry with fallback models
Metrics Collection: Comprehensive performance data gathering

#### STORAGE REQUIREMENTS

Run Storage: 10-50KB per benchmark run
Results Storage: 5-20KB per model result
History Storage: 1-5MB for benchmark history
Cache Storage: 50-200MB for performance optimization cache

#### CONCURRENCY AND SAFETY

Atomic Operations: Safe concurrent benchmark execution
Resource Management: Memory and CPU usage optimization
Error Isolation: Failed model execution doesn't affect others
Data Integrity: Consistent result storage and retrieval

Remember: Citizen, in the resource-constrained wasteland, benchmark commands are your strategic intelligence tools. They provide the data needed to optimize AI usage, control costs, and make informed decisions about which tools will keep your projects running efficiently. Use them to measure, analyze, and optimize your AI-powered development workflow.

DOCUMENT STATUS: Complete

NEXT REVIEW: After AI provider updates

CONTACT: Task-O-Matic Benchmark Team

BENCHMARK COMMANDS

COMPLETE DOCUMENTATION

TECHNICAL BULLETIN NO. 005

BENCHMARK COMMANDS - PERFORMANCE ANALYSIS FIELD OPERATIONS

⚠️ CRITICAL SURVIVAL NOTICE

COMMAND ARCHITECTURE OVERVIEW

COMPLETE BENCHMARK COMMAND DOCUMENTATION

RUN COMMAND

COMMAND SIGNATURE

REQUIRED ARGUMENTS

REQUIRED OPTIONS

GENERAL OPTIONS

TASK CREATION OPTIONS

PRD CREATION OPTIONS

PRD PROCESSING OPTIONS

PRD REFINEMENT OPTIONS

BENCHMARK RUN EXAMPLES

MODEL FORMAT SPECIFICATIONS

BENCHMARK RUN OUTPUT FORMAT

PERFORMANCE METRICS

ERROR CONDITIONS

LIST COMMAND

COMMAND SIGNATURE

LIST COMMAND EXAMPLES

LIST OUTPUT FORMAT

BENCHMARK HISTORY ANALYSIS

OPERATIONS COMMAND

COMMAND SIGNATURE

OPERATIONS COMMAND EXAMPLES

OPERATIONS OUTPUT FORMAT

OPERATION CATEGORIES

SHOW COMMAND

COMMAND SIGNATURE

REQUIRED ARGUMENTS

SHOW COMMAND EXAMPLES

SHOW OUTPUT FORMAT

COMPARE COMMAND

COMMAND SIGNATURE

REQUIRED ARGUMENTS

COMPARE COMMAND EXAMPLES

COMPARE OUTPUT FORMAT

WORKFLOW COMMAND

COMMAND SIGNATURE

REQUIRED OPTIONS

WORKFLOW CONFIGURATION OPTIONS

WORKFLOW STEP OPTIONS

WORKFLOW BENCHMARK EXAMPLES

WORKFLOW BENCHMARK OUTPUT

WORKFLOW PERFORMANCE METRICS

ERROR CONDITIONS

FIELD OPERATIONS PROTOCOLS

SURVIVAL SCENARIOS

TECHNICAL SPECIFICATIONS