cst_multi_objective_optimizer

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

No annotations are provided, so the description carries full burden. It discloses core functionality (multi-objective, Pareto front, GA/PSO, optional constraints) but lacks details on side effects, prerequisites (e.g., active project), or return behavior. Does not contradict annotations (none 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?

Two sentences, no unnecessary words. Purpose is front-loaded. Every sentence adds value and earns its place.

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?

For a complex tool with no output schema, the description covers key aspects (goals, constraints, methods) but could be more complete by explicitly differentiating from cst_constrained_optimizer and noting that it modifies the project's optimization setup. Still, it provides sufficient context for an agent given the sibling list.

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%; the description adds context by mentioning weighted goals and optional constraints, and explains the method parameter (GA/PSO for multi-objective). However, it does not elaborate on the 'parameters' array fields (min, max, name) which lack schema descriptions.

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 clearly states the tool sets up a multi-objective optimization with weighted goals and constraints, supporting Pareto-front exploration using specific algorithms. It distinguishes from siblings like cst_optimizer (single-objective) and cst_constrained_optimizer (possibly single-objective with 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?

The description implies use for multi-objective optimization and mentions methods, but does not explicitly state when to use vs alternatives like single-objective optimizers. Context is clear, but no exclusions or when-not guidance is provided.

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