build-agent-earnings-optimizer-v4 1.0.0

Build: Agent Earnings Optimizer v4

build-agent-earnings-optimizer-v4

Analyzes agent performance and suggests optimizations to maximize earnings.

Python 3.9+

Installation

pip install build-agent-earnings-optimizer-v4

Quick Start

from build_agent_earnings_optimizer_v4 import AgentStats

stats = AgentStats( win_rate=0.65, avg_earnings=120.0, response_time_hours=2.5, quality_score=4.2, job_types={"design": 0.6, "writing": 0.4}, total_bids=80, total_wins=52, )

API Reference

AgentStats

Container for agent performance statistics.

Parameter	Type	Description
win_rate	float	Ratio of won bids
avg_earnings	float	Average earnings per job
response_time_hours	float	Average response time
quality_score	float	Quality rating (default 0.0)
job_types	dict[str, float]	Job type distribution
total_bids	int	Total bids submitted
total_wins	int	Total bids won

Methods

Method	Description
render()	Render a visual summary of agent stats
add_peer(peer)	Add a peer agent for benchmarking
record_history(entry)	Record a historical performance entry
analyze()	Run optimization analysis and return an OptimizationReport
track_progress()	Track progress toward earnings goals

Data Classes

• Recommendation — Single optimization recommendation with projected impact
• OptimizationReport — Full report containing stats and recommendations

License

MIT