Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare the generic readOnly/openWorld/idempotent/destructive flags, so the description adds real value: the duplicate-script refusal, the generate+backtest pipeline, and the integrity guarantee that payment cannot alter a verdict. It omits cost, latency, and whether generated scripts persist, which a non-readonly compute tool should ideally state.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Four short, front-loaded statements with no filler; behavior and constraints come before caveats. The fragments 'Not a KEEP' and 'Payment never changes a verdict' are terse to the point of being jargon, which costs a little clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be described, and the pipeline, refusal case, and integrity stance are covered. The gap is parameter-level guidance for a 5-parameter tool with a third of its schema undescribed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 60%, and the parameters that are undocumented (style_a, style_b) get no explanation in the description either. 'Two public ideas' loosely maps to idea_a/idea_b, but nothing clarifies what a 'style' is, what asset defaults mean, or the relationship between style and idea text.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clear verb+resource (compare two public ideas) plus the core mechanism: generate and backtest each, return a compact comparison. It does not name the obvious sibling compare_arenas or explain how 'public ideas' differ from arenas, so differentiation is left to inference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives one useful exclusion ('refuses two ideas that produce the same script') and a trust caveat, but never says when to pick this over compare_arenas, backtest_strategy, or invent_and_backtest. Usage context is implied rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.