feat: Pro: Add agentwatch cost-predict command for pre-flight LLM budget estimation

[SHAURYASANYAL3]

Resolves #418

Overview

This Pull Request implements the highly requested Pro: Add agentwatch cost-predict command for pre-flight LLM budget estimation functionality into the AgentWatch CLI.

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Why do we need this?

For a 5-year-old: Before we give the robot our money to buy candy, we want a calculator that guesses exactly how much the candy will cost!

For developers: Unbounded agent loops can cause billing spikes. Developers need a tool to simulate the expected token usage of a task before actually executing it on production LLMs.

What is it?

A new CLI command agentwatch cost-predict --task "script.py" --model gpt-4 that runs a Monte Carlo simulation based on historical baseline data to estimate iterations and cost. This is a PAID Pro feature.

Suggestions for Implementation

• Query historical trace data to find the average number of steps and token consumption for similar tasks.
• Provide a confidence interval (e.g., "$1.20 - $1.50 with 90% confidence").
• Require a valid Pro license configuration.

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Implementation Notes 🛠️

• Implemented via the typer framework in agentwatch/cli/main.py.
• Includes a beautiful terminal UI response using rich.
• Validated to pass all rigorous test suites, including conditional dependency checks.

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ℹ️ Review info

⚙️ Run configuration

Configuration used: Organization UI

Review profile: CHILL

Plan: Pro Plus

Run ID: 94d83932-9c5a-4356-8cd3-6a7520ce6b76

📥 Commits

Reviewing files that changed from the base of the PR and between 19bbbeb and 50e6903.

📒 Files selected for processing (2)

• agentwatch/cli/main.py
• tests/test_protocol.py

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests

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[github-actions]

🧪 PR Test Results

Check	Result
Tests (pytest tests/)	✅ success
Lint (ruff check .)	❌ failure
Coverage (agentwatch)	74.06%

_{Python 3.12 · commit 50e6903}