simulation_run_matrix

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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions planning and running hypotheses but omits any details about side effects, permissions, resource consumption, or return format, leaving significant ambiguity for an action tool.

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 concise sentence that front-loads the primary purpose. While it earns its place by being efficient, it could include additional high-level context without becoming verbose.

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?

Given the tool has 4 parameters, no output schema, and no annotations, the description is too sparse. It fails to explain what the comparison output looks like, how results are returned, or any usage constraints like run limits or dependencies on prior steps (e.g., generating agents).

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?

With 50% schema description coverage, the description adds no extra meaning beyond the schema. It does not explain 'rounds', 'research', or 'maxAgents' usage, and only implicitly references 'hypotheses'. The schema already describes that parameter, so the description contributes no new semantic value.

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 plans and runs multiple model-swarm hypotheses and compares outcomes for product-spec decisions, using specific verbs and resources that distinguish it from siblings like simulation_run (single run) or simulation_compare (comparison only).

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 usage for multi-hypothesis comparison, but does not explicitly state when to use this tool versus alternatives like simulation_run or simulation_plan, nor provides exclusions or prerequisites.

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