oraclaw-mcp-server

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

Names specific algorithms (A*, Yen's) implying optimality and k-path behavior, but lacks side effects, complexity, or state mutation details given no annotations exist.

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 concise (9 words) and front-loaded, though 'Optimal routing' slightly redundant with 'A* pathfinding'; could use one more sentence for completeness.

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 provided and description fails to specify return format (path array? cost? multiple paths?), leaving critical invocation information gap.

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?

Baseline score since schema coverage is 100%; description adds semantic context that 'k' relates to 'k-shortest paths' beyond schema's 'Number of paths'.

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?

Specifies A* pathfinding and Yen's algorithm for k-shortest paths, clearly distinguishing from optimization and analysis siblings, though differentiation from solve_schedule could be sharper.

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 this versus solve_constraints, solve_schedule, or optimize_bandit for routing problems.

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