reinvent_sampling

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

With no annotations available, the description carries the behavioral disclosure burden. It discloses dry-run behavior, synchronous execution, immediate return of results, and smiles_file requirements for specific generators. However, it omits details about return format, side effects (e.g., output files), or error handling, which would be valuable for an agent.

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 succinct and well-structured, front-loading the core purpose, then using a compact bullet list for generator modes. Every sentence provides distinct value without unnecessary verbosity.

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's complexity (12 parameters, no annotations, no output schema), the description covers key behavioral and generator-specific requirements but leaves gaps around return value, output handling, and the meaning of several parameters. It is adequate but not complete for an agent to invoke correctly without additional inference.

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 0%, so the description must compensate. It adds meaning to dry_run, generator, and smiles_file (explaining when each is needed), but leaves many parameters (num_smiles, temperature, sample_strategy, output_file, randomize_smiles, unique_molecules, workdir, device) without any explanation, which is insufficient for a 12-parameter tool.

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 opens with 'Generate molecules from a REINVENT4 prior model,' which clearly identifies a specific verb and resource. The generator guide further distinguishes the tool's scope by enumerating four sampling modes, making it distinct from sibling tools like reinforcement learning or transfer learning.

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 provides clear context on when to use the tool, including dry-run vs. synchronous execution, the smiles_file requirement for libinvent/linkinvent/mol2mol, and a generator guide explaining each use case. However, it does not explicitly compare against sibling tools or state when not to use this tool.

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