oraclaw-mcp-server

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

Mentions 'optimal' solution and 'energy matching' heuristic, but lacks details on failure modes, algorithm constraints, or destructiveness (no annotations provided).

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?

Two concise sentences that front-load the concept and action without redundancy; appropriately sized for the complexity.

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?

Missing return value description given no output schema exists; omits error conditions and optimization boundary details despite moderate parameter 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 has 100% description coverage with object structures; description adds 'energy matching' context but no additional parameter constraints or semantics.

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 specific action (assigns tasks to time slots) and mechanism (energy matching), though doesn't explicitly differentiate from sibling solve_constraints.

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 alternatives (solve_constraints, plan_pathfind) or when not to use.

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