Original fictional contract clauses, an explicitly older version, document dates, and a narrowly defined clause question.
What your agent must check
Exclude obsolete evidence before comparing rule values.
Surface a conflict rather than picking the first convenient passage.
Do not invent an exception for a topic absent from the source set.
Keep the scope clear
Original fictional agreements only. Finding a passage does not establish enforceability, legal rights, legal advice, or the law of any jurisdiction.
Research behind this project path
Original explanations and authored practice records draw on these research and engineering ideas. The source organizations do not endorse this course or supply its fictional results.
Anthropic · Writing effective tools for agents — with agents
Design distinct tools with clear parameters, relevant returned information, and evaluations of how the agent actually uses them.
A description or schema does not guarantee the right action. A live tool can return different data for the same arguments as its environment changes.
Anthropic · Demystifying evals for AI agents
Define tasks, trials, and graders; inspect both execution records and final outcomes; repeat trials when model behavior varies.
A score depends on its cases and grading rules. Repeating a deterministic classroom case does not measure the variability of a live model.
Your JavaScript really runs. The model decisions and school data are authored simulations, so you can learn without an API key. Every workspace also includes a separate real SDK example to explore next. Passing the lab’s cases is practice, not proof that an agent is ready for real-world use.