oraclaw-mcp-server

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

Lacks annotations and fails to disclose computational cost, random seed behavior, or correlation matrix requirements beyond method name drops.

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?

Extremely terse (fragment format) but information-dense with no filler; arguably too minimal for complex financial domain.

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?

No output schema exists yet description fails to explain return values (single metric? matrix? distribution?) or side effects.

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 has 100% description coverage; tool description adds no semantic value beyond structured field definitions.

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?

Clearly identifies portfolio risk domain and specific methodologies (VaR/CVaR, Monte Carlo) distinguishing it from generic simulation tools.

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?

No guidance on when to use versus sibling simulate_montecarlo or other optimization/analysis tools.

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