simulation.plan

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

With no annotations, the description carries the full burden. It discloses key behaviors: local execution, adapter switching, default behavior without live models, and return structure. It could mention whether anything is persisted or side effects, but it is transparent about the core behavior.

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 concise (~90 words) and well-structured into a purpose statement, prerequisites, behavioral notes, and return value. Every sentence adds value without repetition.

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 large sibling set, the description covers prerequisites, output structure, and core constraints. It could better explain how this planning step fits into the broader simulation workflow (e.g., leading to simulation.run).

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 description coverage is 100%, so the baseline is 3. The description adds context about adapter defaults and the optional research JSON, but does not significantly enhance parameter meaning beyond the schema.

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 states a specific verb ('Create'), resource ('clean-room product simulation scenario'), and source ('Memoire research evidence'). It clearly distinguishes from siblings like simulation.run and simulation.compare, which execute or compare simulations.

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?

Prerequisites are explicitly stated (research data location or passing a JSON string). It clarifies what the tool does not do (does not call MiroFish) and recommends adapter usage. However, it does not explicitly list when to use this tool versus alternatives.

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