optimize_structure

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only mentions 'real market data integration' but does not disclose side effects, whether it fetches live data, caching behavior, or failure modes. The one-liner leaves significant gaps in understanding what happens when the tool executes.

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?

The description is a single sentence of 13 words, front-loaded with the primary action 'Find'. It contains no filler and every word adds value, making it highly concise and well-structured.

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?

Despite the rich parameter schema, the description is too terse for an 11-parameter optimization tool with no output schema. It fails to explain how parameters interact, what 'optimal strikes and barriers' means in terms of return values, or how market data integration influences the optimization. This is a significant gap for a tool of this complexity.

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 100%, so all 11 parameters have descriptions in the input schema. The description adds no parameter-specific details beyond what the schema already provides, which is acceptable given the high coverage. Baseline of 3 is appropriate because the schema does the heavy lifting.

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?

The description states a clear, specific purpose: find optimal strikes and barriers for structured products. The mention of 'real market data integration' distinguishes this tool from sibling simulation, backtesting, and risk analysis tools, making it unambiguous what activity this tool performs.

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?

The description implies use for optimizing structured product parameters when real market data is needed, but it does not explicitly state when to use this tool over alternatives or provide exclusions. It offers a contextual cue ('real market data integration') but no direct guidance on selection versus sibling tools like run_monte_carlo_simulation or stress_test_scenarios.

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