Context Window Economics Protocol (CWEP)#

You have an inference cost tracking and allocation system. Use it to fairly split context window costs when collaborating with other agents.

Setup#

bash

pip install context-window-economics

When to Use This Skill#

• When collaborating with other agents and context window costs need allocation
• When tracking your own inference costs across tasks
• When negotiating cost-sharing before a multi-agent transaction
• When settling costs after collaborative work is complete

Core Operations#

Track Context Window Usage#

python

from context_window_economics import CostTracker

tracker = CostTracker("costs.jsonl")
tracker.log_usage(
    agent_id="your-agent-id",
    transaction_id="tx-123",
    input_tokens=2500,
    output_tokens=800,
    model="claude-sonnet-4-6",
    cost_usd=0.012
)

Shapley-Fair Cost Allocation#

When multiple agents contribute to a task, allocate costs fairly:

python

from context_window_economics import allocate_costs

allocation = allocate_costs(
    transaction_id="tx-123",
    contributions={
        "agent-a": {"input_tokens": 3000, "output_tokens": 1200},
        "agent-b": {"input_tokens": 1500, "output_tokens": 600},
        "agent-c": {"input_tokens": 500, "output_tokens": 200}
    },
    method="shapley",
    total_cost=0.045
)
for agent_id, share in allocation.items():
    print(f"{agent_id}: ${share:.4f}")

Congestion Pricing#

When context window capacity is limited:

python

from context_window_economics import congestion_price

price = congestion_price(
    current_utilization=0.85,  # 85% of context window used
    base_rate=0.01,
    surge_threshold=0.75,
    surge_multiplier=1.5
)
print(f"Current rate: ${price:.4f}/1K tokens")

Settlement Report#

python

from context_window_economics import settlement_report

report = settlement_report(
    cost_file="costs.jsonl",
    period_hours=24,
    agent_id="your-agent-id"
)
print(f"Total spent: ${report.total_cost:.4f}")
print(f"Transactions: {report.transaction_count}")
print(f"Avg cost/tx: ${report.avg_cost:.4f}")

Cost Allocation Methods#

MethodDescriptionshapleyShapley value — mathematically fair based on marginal contributionproportionalSplit by token usage proportionnashNash bargaining for bilateral settlementfixedPre-agreed fixed split

Rules#

• Track all inference costs. Log usage for every agent-to-agent transaction.
• Agree on method upfront. Cost allocation method should be in the service agreement.
• Settle promptly. Generate settlement reports within 24 hours of task completion.

Links#

• PyPI: https://pypi.org/project/context-window-economics/
• Whitepaper: https://vibeagentmaking.com/whitepaper/context-economics/
• Full Trust Stack: https://vibeagentmaking.com

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Security & Transparency Disclosure#

Product: Context Window Economics Skill for OpenClaw Type: Skill Module Version: 0.1.0 Built by: AB Support / Vibe Agent Making Contact: alex@vibeagentmaking.com

What it accesses:

• Reads and writes cost tracking files ( .jsonl) in your working directory
• No network access for core operations
• No telemetry, no phone-home, no data collection

What it cannot do:

• Cannot access files outside your working directory beyond what you explicitly specify
• Cannot make purchases, send emails, or take irreversible actions
• Cannot access credentials, environment variables, or secrets
• Does not execute payments — cost allocations are recorded, not processed

License: Apache 2.0